StartupYard Alumni

SY Alumni Talk about the Value of StartupYard for Them

This week, the popular podcaster Florian Kandler, of Startup Milestones, published another video with a pair of StartupYard Alumni from 2015: Jakub Ladra, of Claimair, and Ondrej Sedlacek, of Satismeter. Through the course of the talk, the two founders focus on the core value of acceleration at StartupYard, what their personal experiences were during acceleration, and what advice they would give to other founders thinking about joining.

The pair also jump into a discussion of what to look for in a good accelerator, and other tips for pre-accelerator startups.

StartupYard Alumni Talk Acceleration:

 

Key Takeaways:

  • Ondrej Sedlacek (Satismeter)
    • You need to find an accelerator that has the appropriate focus for you.
    • Mentorship is about recognizing patterns between different conversations, but also about learning how to communicate your ideas more clearly.
    • The biggest single value is simple: great advice. The impact of that advice from mentors, investors and the SY team is increased because of the compressed timescale of acceleration. You are forced to make decisions quickly.
    • Setting clear goals for yourself also helps you to use the advice of mentors and advisors better: focusing them on what you need.
    • Good accelerators attract investors who look at every startup in the program. Your chances for investment rise thanks to your participation.
    • The StartupYard program helped to narrow the focus on the product, and think in terms of execution and milestones.
  • Jakub Ladra (ClaimAir)
    • Mentoring is uniquely intense and important for building your network. Connections made there can last and change your business over time.
    • You talk all day about your value proposition, and this is a big challenge. We had no idea how intensive this repetition and iteration can be.
    • Management team meetings at StartupYard reinforce learnings from mentors, and bring up new unexplored ideas.
    • The act of prioritizing between ideas during “mentoring madness,” was deeply valuable. The ongoing discussions were a big challenge, but worth the time to go through.
    • The accelerator is especially important in helping a startup scale: laying the legal, technical, and strategic groundwork for sustainable growth.

 

You can now apply for StartupYard Batch #8.

  • Robots
  • Artificial Intelligence
  • VR/AR
  • IoT
  • Cryptography
  • Blockchain
Applications Open: Now
Applications Close: June 30th, 2017
Program starts: September 4th, 2017
Program ends: December 1st, 2017
Ada Jonuse, Startupyard, Lithuanian startups

Ada Jonuse: Lithuanian Startups Need to Think Bigger

 

I will be heading to Lithuania for the first time on May 25th to mentor startups and host a workshop at LOGIN Startup Fair, in Vilnius. As you may know, StartupYard has only ever accelerated one startup from Lithuania, the Slovak/Lithuanian team behind Feedpresso, the AI enabled news collection and curation app (which I also use myself).

Ahead of my trip, I caught up with Ada Jonuse, a well known figure in the Lithuanian tech community, and an advocate of women professionals in the technology sector. Ada has been an event organizer in Lithuania for many years, and has worked in the European Parliament, including as the head of the office of MEP Antanas Guoga from 2012-2014, where she organized #SWICTH!: international event on ICT and entrepreneurship in Vilnius. September 2016: with 10.000 participants, the event garnered the Guinness World Record of the biggest programming lesson in the world.

Here’s what she has to say about Lithuania, the tech scene there, and more:

Hi Ada, you’ve worked in the European Parliament, founded several IT education initiatives in Lithuania, and you “gather talented women in tech.: Tell us a bit about yourself, and why do you what you do.

Right now my main occupation and passion is being CEO and co-founder of Lympo.lt. Lympo is a platform which helps to find the best personal trainers near you and I have a vision that it will gradually evolve to a general global talent sharing platform. We want to make money-free exchanges possible with Lympo points underpinned by blockchain technology.Lithuanian Startups, StartupYard, Ada Jonuse

Actually, I always wanted to become a politician and this is why I returned to Lithuania after 10 years abroad. It did not quite work out as expected as the party I was running with for parliamentary elections got involved in a massive corruption scandal. During my years in the European Parliament I had an opportunity to work with a talented entrepreneur turned politician (and a poker star!) Antanas Guoga. He inspired me to join Lympo and this is how I found myself in a world full of new discoveries.

When I recruited first team members for Lympo in December, I had no idea what the difference between back-end and front-end is. 🙂 For me, leading a startup is a big responsibility and a commitment to never stop learning.

StartupYard is headed to Vilnius for the first time this year, for the startup fair at LOGIN. What should we expect from Lithuanian startups? What are their key strengths?

LOGIN is a great event and I am very glad you will be visiting Vilnius. You will be surprised that Lithuanian startups don’t actually have to be Lithuanian: their founders, CTOs and key developers might be coming from Ukraine, Belarus or Russia. This talent influx made the startup ecosystem in Vilnius much more interesting. You should expect tech-heavy companies focussing on providing various niche B2B solutions: it could be, for example, VR, big data, medtech, fintech. The key strengths are very talented engineers, hard working teams and drive towards perfection. On the other hand, they might lack business development or global strategy elements.

When people think about the Baltics and tech, it’s usually Estonia front and center. Would you say Lithuania is following in Estonia’s footsteps, or making its own path forward? What does Lithuania lack that Estonia has, and where are Lithuania’s advantages?

Lithuania is on its own path. In recent years, we concentrated on enabling fintech companies to thrive in Lithuania. The Bank of Lithuania did a great job and now the country has one of the most innovation friendly regulation systems in Europe. Another big topic is gaming industry. Lithuania attracts a lot of IT talent from Russia, Belarus and Ukraine. Great gaming talents could make Vilnius a strong gaming hub. What Lithuania lacks in comparison to Estonia is obviously a big success story like Skype and all the experience and connections that came with it. So far, we also lacked a proactive government that makes digital innovation its top priority.

Lithuania is a small country, and sadly many Europeans don’t know much about it. What do you wish more of the European community knew about the character of the country, the people, and life in Lithuania?

It is natural that a country of 3 million people is difficult to remember. I wish Lithuania was known more for its amazing nature. We have superb quality air, water, lots of space and fresh and healthy natural food. I love gathering wild berries in the endless forests of Lithuania. It is such an exceptional experience. Most people in the world are deprived of these crucial elements of good life. I started appreciating this a lot after my traineeship with the UN in Kathmandu, Nepal, which is one of the most polluted Asian cities.

Estonia has cultivated a strong reputation for an innovative government, in addition to the private tech industry. Has this had a big influence Lithuania as well? How does the government relate to the tech ecosystem?

Lithuanian government is very innovative in the fields of e-government and digital services for citizens. This works great. Much better than in the majority of EU countries. However, on the larger scale I miss more strategic government actions. Let’s take education: IT education in schools is old fashioned and starts way too late. At the same time, there is a huge lack of developers in the country. I personally constantly struggle to find people. Therefore, I co-founded an initiative to provide every Lithuanian fifth-grader with a BBC micro:bit microcomputer in 2017. Lithuania is celebrating 100th anniversary of modern statehood next year and this will be our gift for the upcoming 100 years!

On the same theme, how does Lithuania compare with the rest of Europe in terms of conditions for entrepreneurs, in things like taxation, bureaucracy, and legal complexity? 

Within Europe I had a chance to live in Germany, Belgium,  the UK and Italy. I dealt with bureaucracy in all these countries. Now, back to Lithuania ten years later I realize how simple our bureaucratic system is. It took us less than 2 days to establish a company and we didn’t use any paper at all! When it comes to taxation, as an entrepreneur I have one single wish for the Lithuanian government: tech companies must have tax exemptions for the first year. In order to pay an employee 1500 EUR I have to spend 2600 EUR. This is killing startups.

As mentioned, you founded W@Tech, a platform for professional women in tech. Would you say the Lithuania and the Baltic states generally are doing better, or worse than the rest of Europe when it comes to being inclusive?

I am right now part of an amazing project – Women Go Tech mentorship program which connected me to a wonderful mentor Darius Montvila. The very fact though that this program exists shows that we lack women talents in Lithuania as well as in the rest of the world. Having in mind that women are top users of many tech products, from social media networks to e-commerce platforms, it is staggering that only 17% of startups have female founders.

W@Tech aims to make these names known and show more role models to inspire younger generation. Together with W@Tech, I plan to organize a conference on VC startup financing in Berlin this autumn. It will be almost impossible to find female VC speakers, but we will do all it takes to at least uncover some names.

What would you say are two or three of the top challenges for Vilnius as a tech ecosystem today, and what are local entrepreneurs, investors, or the government doing about them?

Number 1 challenge is a lack of global mindset and network. There are so many startups that aim to operate in the Lithuanian market. It is simply too small. Entrepreneurs don’t have connections to big tech hubs like Silicon Valley, London or even Berlin. Number 2 challenge is related to that. It is a lack of big ambitions. As access to finance is difficult, startups must make money as soon as possible, but they need to find a business model and grow first. Big ideas have to find markets for their expansion. Government played an important role in securing more IT talent by making visas for non-EU citizens easier. We even have a startup visa now, so the whole startup can migrate to Vilnius with the assistance of the city and the government.

Big ideas have to find markets for their expansion: @adajonuse on #Lithuania #startups Click To Tweet

You can now apply for StartupYard Batch #8.

  • Robots
  • Artificial Intelligence
  • VR/AR
  • IoT
  • Cryptography
  • Blockchain
Applications Open: Now
Applications Close: June 30th, 2017
Program starts: September 4th, 2017
Program ends: December 1st, 2017

For you, what are the two or three biggest successes in tech to come out of Lithuania in the last few years? What parts of the tech ecosystem show the most promise going forward?

 

One of our great successes is  a mobile social marketplace for secondhand clothing with more than 11 million users and its top market Germany. Actually, the co-founder and CEO of Vinted, Justas Janauskas, is advisor to my company Lympo. We learn so much from Justas. I believe that more successful companies should mentor young startups in Lithuania. [Vinted secured 27M Euros in VC funding in 2015]

I also admire Trafi – a public transport app based on machine learning, data from the crowd and self-learning. It was the official public transport app for Olympic games in Rio. Last year, Trafi launched a partnership with Uber for connecting public transport with Uber services.

When it comes to fintech, I have to mention the Bitcoin wallet SpectroCoin. It has achieved great results last year.

Top 3 #startups in Lithuania to watch via @adajonuse: @trafiapp, @vinted and @spectrocoin Click To Tweet

It is a bit unfair, but I must mention two exciting companies I work with myself: PM Screen producing 3D holograms and interactive screen apps with amazing projects in the US and Dubai; and a.lot parking – a parking technology company that aims to transform parking industry in the US. With license plate recognition technology so common in Lithuania, we want to ensure seamless parking experiences and even enable everyone to rent out their private parking space in a garage.

So, you see, the variety of companies is huge: from marketplaces to machine learning and fintech. And then there is a big lot of niche B2B tech startups working with big data, sensor technologies, 3D printing and much more.

What would be your 3 top reasons for visiting Vilnius (or other parts of Lithuania), and what are a few things a visitor simply has to do there?  

 

I love Vilnius. It is my home town and honestly one of the best places in the world. Vilnius has a charming medieval old town, a great bar scene and vibrant cultural life. People here might not smile a lot, but they are very helpful and sincere once you get to know them a bit better. I would propose to discover some great street art and the atmosphere in the upcoming part of the town, Naujamiestis, close to the train station; to take a balloon flight during one of the fantastic summer sunsets and to simply try to get lost in the narrow streets of Vilnius. You will discover so much.

SY Podcast: Mergim Cahani, Founder and CEO of the Fastest Growing Tech Company in the Balkans

Tomas Tunys, StartupYard

This Machine Learning Geek Thinks You Need StartupYard

Tomas Tunys: Machine Learning Geek

Tom Tunys is the “silent one,” of the Rossum.ai team. He is a prototypical machine learning geek, which is to say: quiet, thoughtful, and rigorous in his thinking. He joined StartupYard along with co-founders Tomas Gogar and Petr Baudis, two also geeky, but comparatively outspoken AI/ML geeks in their own right.

As StartupYard focuses on AI/Machine Learning startups and founders for our upcoming round of acceleration (applications close June 30th), I reached out to Tomas to talk about his experience at StartupYard. Tomas is, as he would say, not a business minded person. This is the story of how he came to appreciate his experience at StartupYard despite initially doubting its value.

Here is what he had to say:

Hi Tomas, you have always been the quiet member of the Rossum.ai team. Can you tell our readers how you joined Rossum, and your background in Machine Learning and AI?

Tomas Tunys, StartupYard

It’s almost a year since the moment Tomas, Petr, and I were discussing the possibility of creating our own startup, but our history together is much longer than that, so let me briefly tell you my story, and how we met.

In late 2012 I started my PhD studies at the Czech Technical University, under the Cloud Computing Center research group led by Jan Sedivy. It was there where the team behind Rossum first met (albeit not all at the same time). We all together worked on a dozen different machine learning applications, supervised students, and helped to build up what is now known as eClub Prague. To sum it up we have known each other for more than 3 years now.

When I think about it I started my PhD back then out of love for mathematics, optimization and machine learning that had built up in me doing my master’s thesis. I should say that prior to that I had no background in machine learning whatsoever but I could always appreciate the beauty and elegance of mathematics and optimization.

Since I had no clear idea what to work on I laid my hands on many different machine learning topics such as document classification, topic modeling, information retrieval, and learning to rank. The last mentioned has become the main focus of my research and it is about developing algorithms for sorting “things” in a particular order such that the final list has the desired property. One example for all would be a web search where you might try to order the list of documents for a query in a way optimized for user satisfaction.

To me this has always been about the act of accomplishing new things in a very intellectual way. What’s strange about my journey to Rossum and StartupYard is that I am really, really not a business guy. Not at all. I just love math.

You’ve described yourself as someone who finds the business aspect of technology unappealing. You’re very critical of business culture. What motivates you to do the work you do, and what do you hope will come from it?

Quite simple to answer: I do what I do because I love it, and moreover I work with amazing, smart, and genuine people which I see as an endless source of inspiration and motivation.

What am I working on right now? I am part of the research and development team in Rossum which is currently building a machine learning engine capable of reading and understanding the content of textual documents on a human level.

This is of course a far-fetched goal (yes, even now with the current level of technology) and we wanted to make a business case out of it right now, not really building a business on empty-handed promises.

We know that we need to take small steps, like the saying “you need to learn how to walk before you can run” (I can imagine a business person would use fly instead of run without hesitation here), so we decided to focus on understanding a particular instance of documents, which are invoices. I’ll leave what we do in Rossum at that, you can find out more at rossum.ai.

What I hope will come out of our work? My only hope is that in the end we built something amazing that everyone can benefit from.

I am of course looking far into the future, but just imagine what can be done with a technology that can go through gazillions of documents accumulated throughout our history, such as research articles, medical reports, legal documents, books, newspapers, internet -take your pick- and provide access to knowledge, not only information, hidden inside them.

How much can research be sped up? How many lives could be saved? How many hours could be spared at court (sounds stupid unless you know how the Czech judiciary system works)? The list may go on. And I know I chose words that make this sound totally abstract and unspecific and I made it deliberately, because it would be really hard for me to formulate concretely what I mean by “access” (interface specification) and “knowledge” (data store and inference engine).

This is something we will be more than happy to contemplate at Rossum.

We had a discussion recently about the impact that AI/ML is having and will have on humanity and society. Can you talk a bit about your perspective on the role AI will play in our lives going forward?

I think that ML already plays an important and maybe irreplaceable role in the everyday life of a modern person and it is going to be more so in the future.

So far ML (Machine Learning) is mostly prominent (and this is solely how I see it, and might be wrong) in the realm of the internet. Web search, social networks, e-commerce, all these services are intertwined with ML algorithms which are programmed to make a user more satisfied, more engaged, click more, purchase more, etc. But ML is going to have a big voice in “the real world” pretty soon (Do not ask what soon means!), for example, Tesla with its self-driving cars.

This big shift is going to make Machine Learning something that more people can directly benefit from. ML works best wherever there is the most data to leverage. That has meant the internet, and advertising, and so forth, but soon it will mean anywhere there is a sensor and a stream of data coming in. It is hard to imagine the range of applications that will propagate from the Internet of Things.

Let’s play for a bit on a more futuristic and philosophical note, because such a question always deserves it.

In my opinion, it is just a matter of time before AI reaches and supersedes the human level of performance in every aspect. There is nothing that would suggest otherwise, on the contrary, and that makes me think what would be there left for humans?

Everyone kind of says, there will always be something left, without having any clue what that something might be, which does not give me a lot of comfort. I fear that in the end AI will rob us of our curiosity, which I reckon is the main driving force of human progress (definitely of mine). Just think about it, there is no way anyone would wait for you to find answers which are already there (definitely not in a business)  – the only person that would need to resist going for the shortcut and get the answer from your pal HAL, is you.

Sadly, I do not see people nowadays willing to ponder over even the simplest of problems, stackoverflow-copy-paste simply wins (if you are a programmer you know what I am talking about). Now imagine there is an omniscient stackoverflow — disaster is in our way! Is there a solution or is it even a problem that needs solving? I do not know what it is for you, but I’d rather stay curious.

We also talked about the nature of intelligence, our assumptions about our own intelligence, and the capabilities and benefits/drawbacks of AI. What do you think most people are getting wrong in our understanding of these topics?

Let me share with you some of my thoughts on how some of us may see their own intelligence and relate it to the idea of (general) AI.

I think that people tend to think about themselves and their intelligence as something superior, and (so far) unmatched, yet I do not think there is an agreed upon concept of AI. There is definitely more than one, hence, for me there is not a firm ground to base a comparison on. How do we define general AI if we don’t understand what makes us intelligent to begin with?

But this sort of an egoistic self-regard, a proclaimed superiority in terms of intelligence that should definitely not become part of the AI we are trying to build. Because if you stop for a second to think about how we treat the runner ups in this ridiculous game you would not want to become a runner up.

Machines can replace humans, like machines have replaced humans throughout history. But there is an important distinction: the machines do not replace humans by doing exactly what humans used to do. Hand-sewing was replaced by the loom. Hand crafting of parts has been replaced by machine tools and moldings, and now 3D printing. The machines that replace humans don’t function the way we do, or produce exactly the same results we would.

So when we consider machines replacing humans, a mistake we can make is to imagine that the process or the product carries on as it did before. But that doesn’t happen. The process and the product are changed, and we as a society and different industries adapt to those changes out of necessity or convenience. If something used to be handmade out of wood, but is now made of plastic, we accept this change because of the cost savings, or because of the superior qualities of the plastic.

We don’t think much about the kaleidoscopic effects of those changes. Industrialization helped create products that couldn’t be imagined before. A car or a plane are just a machine, but now they shape the way that all of society functions.

That same process happens also in services. We had bank-tellers, but people accepted a less personal approach in order for the convenience of cash machines. Bank-tellers became fewer and more specialized. Call centers and phone operators are another case of this. Soon it will apply to more professions. The outcomes will be different, but it will be about what people are willing to accept- not about exactly reproducing the same results using AI.

Today we do not understand what those results will actually be. We cannot know, just like we couldn’t know what the results of the industrial revolution were going to look like. Some huge positives, for sure, but also some big, big negatives.

A big mistake I have heard from people, some of whom invested a lot of money into the research of general AI, is that they can make sure to build AI that obeys certain rules of conduct.

Nothing can be further from the truth and we, humans, are the best example. When you are a parent, you may try your best to control for all the factors that can influence your child’s growth (external factors could make this a false analogy, but I do not think so), but there is no way of saying for a 100% certainty that a child will become a nobel prize winner or a serial killer. The problem when it comes to AI is the latter.

You cannot predict how something will evolve when it is inherently as complex or more complex than you are. No simulation or set of rules can account for all variables when you don’t know what all the variables will be.

By this I am not implying we should drop the idea of developing general AI. I am saying that we should become really careful parents for the AI we want to raise. In the end we need to hope for the best (or just roll the dice) when we decide to let it go into the world.

I guess most people also see AI as something that is bound to become evil. But this also begs the question: what is meant by evil? This is a favourite theme recurring in literature and movies and I am talking about it mainly to mention a particular one — R.U.R. by Karel Capek — where Rossum gets its name from, which also kind of gives away what we plan for the future (just kidding?).

You’ve said that you initially were very skeptical about StartupYard, but that now you would recommend the program to others like yourself. What changed?

I experienced StartupYard! That’s what changed. I guess my skepticism about StartupYard stemmed from my ignorance and lack of a “business” gene.

When we joined StartupYard, I suspected that it would be a distraction and a waste of time. I want to work on AI/Machine Learning, and not talk about working on AI/Machine Learning. So for me that’s a struggle, and one I still experience.

The Rossum Team: Petr Baudis (left), and Tomas Gogar (middle), with Tomas Tunys (right)

But on the other hand, for the other members of our team, Petr Baudis and particularly Tomas Gogar, I saw incredible changes in their thinking, and really noticeable growth in their abilities outside of the technology we are working on. The other Tom definitely has the business gene, and StartupYard brought it out in him and made him much more confident, and much more wise about the business, and all the challenges we face.

Honestly, I would be lying to say that this was an experience that transformed me as a person, but as a team we were quite transformed. We began to work with much more focus, and so much more effect, on problems that are going to help us grow and keep climbing new mountains.

I can see the difference between our mentality at the beginning, and our mentality today, and it is remarkable.

What would you say to someone like yourself, who is deeply invested in advancing new technologies, but doesn’t believe that an accelerator StartupYard is what they really need?

Well, I don’t want to make a case out of myself, but I would say this:

If you are on your own and you want to do business for whatever reason, then you definitely need something like StartupYard.

I am not a sell out. I will not claim StartupYard is the best thing that can happen to you, but I will say that from my experience the whole team behind it does its best to shape your idea (or if you have none, it helps you to formulate an idea) into a real and viable business.

It does so by providing access to a vast network of mentors, which you certainly do not have and who are non-technical for the most part. In the end many of these mentors can become your potential customers, while others can come up directly/indirectly with an opinion or an idea that can really move you forward in your own thoughts. Moreover, StartupYard teaches you how to think about your business and prepares you on how to talk and present your ideas appropriately. That’s the most crucial part: getting others to understand clearly what are you bringing to the table.

I guess I read this on the StartupYard blog, but I grew fond of it: you and your ideas need to be the fire and StartupYard is the gasoline that makes it go big. I know it sounds like a cliche, but the people behind StartupYard really live up to that message.

And if you are a part you a bigger team, where the others are eager to take over the business part and you have the luxury to concentrate on what you love, then it would really depend on the others, but after seeing the personal growth of Petr and Tomas after going through StartupYard, I can only recommend taking that chance and joining.

You can now apply for StartupYard Batch #8.

  • Robots
  • Artificial Intelligence
  • VR/AR
  • IoT
  • Cryptography
  • Blockchain
Applications Open: Now
Applications Close: June 30th, 2017
Program starts: September 4th, 2017
Program ends: December 1st, 2017
Blockchain, StartupYard,

Blockchain Founders Need StartupYard: SY Alum Dite Gashi

Dite Gashi is the founder and CEO of Decissio, the blockchain powered investment management and smart-contracts platform that was accelerated at StartupYard this year. Dite has called Decissio the “Jarvis” of investment decision making. The company is working to build a data platform that helps venture investors and professional portfolio managers to actively manage their investments, based on blockchain verified and real-time data.

Dite has been a leading voice in the blockchain movement for years, and represented the first startup at StartupYard to focus on the technology. I caught up with Dite this week to talk about the future of Blockchain, and why startups in the space need accelerators like StartupYard now more than ever. Here’s what he had to say:

Hi Dite, you’ve been working with Blockchain technology for almost as long as it has been around. Tell us how you got into Blockchain, and why it still fascinates you.

Decissio, StartupYard

Dite Gashi, left, participating in StartupYard’s voice training workshop

Blockchain has been an obsession of mine from when it came out as a research paper, all the way up to Bitcoin and Ethereum. My background is in computer science, business management and economics. This knowledge base, fueled by curiosity, allowed me to dive deeper into blockchain concepts first and then into their applications in the world of business quicker than the mainstream world, which to this day I believe has a superficial understanding of blockchain as an innovation.

What doesn’t the mainstream business world understand about Blockchain?

Most of the mainstream business world seems to be in a state of needing to get a piece of the action when it comes to this technology. I’ve literally heard phrases like – we are talking to you because our CEO said “we need blockchain.”

Why 'we need Blockchain' isn't a good reason to work with most Blockchain #startups - Dite Gashi… Click To Tweet

The fear of missing out is big. I’d go as far as to say that’s the money that keeps most blockchain startups running. Wanting to be part of the new revolution is totally fine, however the way that they go about it tends to be sub-optimal. Investors sometimes invest in shady schemes and promising ICO’s (Initial Coin Offering) without proper tech due diligence and auditing, just to find out a few months down the line that the tokens they got are suddenly worthless.

I think the greatest misconception lies in not understanding the basic utility that blockchain provides, which in most cases boils down to somehow cutting out the middle man. Only after understanding it, can you think of an investment opportunity through the filter of whether a blockchain application would be the best for that particular purpose. There are many applications out there who would do fine without blockchain.

You attended StartupYard as part of Batch 7 earlier this year. What do you think that other founders with Blockchain ideas can get out of StartupYard?

Having been present in the blockchain sphere for a while I can attest that most blockchain people tend to be technologically inclined, or as the world likes to call them, nerds. They have strong technical skills that they apply or a great ability to understand and aim to solve important problems. I believe that is great for building technology blocks, innovating and bringing about thought provoking questions of alternate models of functioning.

Where the blockchain community does fall short though is the ability to reach out to people. I believe blockchain founders can learn about marketing, how to sell and how to communicate with masses. They can better refine their offerings to match the needs of the market – something that many startups miss.

Right now we are seeing a sort of valley between the promise of Blockchain innovation and the realities. Right now, the technology is too geeky and complex for ordinary people to use, and too fringy and speculative for corporations to really get behind it. A team I put together last month took 2nd place in the KB Fintech Hackathon in Prague, working on a blockchain contract verification system, so it’s obvious that banks are starting to see real potential in the technology.

Still, we are in the very early days, and blockchain founders are going to need a lot of exposure to the perceptions and expectations of existing industries, in order to come up with solutions that have a chance of being adopted widely. StartupYard is an ideal environment for a really speculative technology to come face to face with the hard reality of the market. I think Decissio is a perfect example of that: all the traction we’ve gained has been thanks to the feedback we got directly from potential customers at StartupYard.

What do you see as the biggest barriers for Blockchain founders right now?

Probably more than any area in tech in recent history, blockchain does have a credibility problem. A big part of that has been the ongoing saga of Bitcoin, which has unfortunately attracted a lot of negative attention. Rightly so, I think, because Bitcoin brought some of the worst elements to the blockchain community, and became an attractor for the get-rich-quick schemers and for cyber-criminals and extreme political ideologues.

Actually this is nothing new: the internet itself did basically the same thing in the 1990s especially, and it suffered its own credibility gap, until serious, in-depth businesses started to make the web safer and more usable for regular people and business. Any really disruptive area of technology has this cycle built in. Now we need serious, sober thinkers to apply themselves to making blockchain useful in real life, and not just in fringe communities. That is a blocker for good people to take Blockchain technology seriously, and a blocker for them to pitch new blockchain ideas in the business and consumer worlds.

This is also a reason why I see StartupYard as a great platform for serious Blockchain innovators. Working with an accelerator like StartupYard brings much needed credibility to ideas that many would-be customers and partners might not take seriously. But with StartupYard, you have a chance to be heard by the right people, and given a chance to convince them you’re doing something interesting.

What was your biggest surprise attending StartupYard? What were you not expecting to change?

The biggest shock for me was to figure out how mainstream customers (in my case, investors) think in relation to products and services they purchase. We tend to turn it into a complex equation, however it boils down to really simple factors when facing a buying decision.

'At Sy I learned that mainstream customers don't buy technology. They buy solutions.' -Dite Gashi Click To Tweet

I believed that I could relate to customers and if we had a great technological products sales would soar. That is the case sometimes, however if you can’t really explain how it relates to people you are selling to, the product is a lost cause. I thought I was good at that, but being faced with mentors, customers and advisors it is obvious that I had a lot of catching up to do – which has lead to tremendous growth of knowledge on my end.

What do you think are the biggest weaknesses in the Blockchain community, when it comes to turning new ideas into businesses?

Blockchain is a maturing technology that has tremendous potential. I like to make comparisons with the early days of cloud computing – companies like Dropbox, Amazon Web Services, Azure capitalized on new technology breakthroughs, and built great products. Blockchain has the potential to be as transformative as cloud computing in the near future.

When you really look at it, Blockchain can form the backbone for a whole new way of looking at the web. There are really not many areas of commerce or government, or even interpersonal relationships, that Blockchain won’t touch. Imagine things like credit card fraud or political corruption being impossible, because at every level, monetary transactions and activities can be audited by powerful AIs. Imagine democratic processes that are un-hackable, or messaging systems that are impossible to hack into. Scary ideas for some people, I’m sure, but an amazing vision of the future for most of us.

The internet has created unprecedented prosperity, but also unprecedented opportunities for fraud and abuse. Blockchain technology, or something very much like it, may be the answer as to how we move forward into a trust based society, where everyone has really powerful tools for protecting themselves and being treated fairly.

'Blockchain is like cloud-computing. It can change everything.' - Dite Gashi on #Blockchain… Click To Tweet

I believe there are many disruptive blockchain applications and companies waiting to be built by ambitious founders. The weaknesses that community faces is monetization. Many blockchain ideas sound good on paper, however for an idea to work and thrive it has to benefit all stakeholders involved, including founders and investors. With the cloud, there was also a learning curve around how it would be monetized: there was uncertainty about where the defensible value of new products was, be it in hardware or software. Blockchain has the same issue, only more so: it is about distribution and de-centralization, which makes it more complicated to create a business model around it.

It doesn’t help that blockchain people seem to be a part of a bubble and are often isolated from actual customer needs. Disruptive technology needs to have people behind it that really understand the customers whose industries they are disrupting. As became very clear to me working with the mentors at StartupYard, just because we see ourselves as creating new technologies, doesn’t actually mean that customers see us that way: people rarely buy technologies, they buy solutions to their problems, in whatever form that takes.

What would you say to a Blockchain startup founder who is thinking about applying to StartupYard?

Having blockchain experience I receive loads of requests for consultation ranging from technology architecture to cryptocurrency trading. It has led me to grow a bit reluctant to provide strong advice, just because the field is changing so often and I would like to be accurate with my proposals.

However in the case of StartupYard I am 100% convinced that it would benefit a blockchain founder tremendously. Trust me on this one, do it and then thank me later.

While at StartupYard I would encourage them to go in with an open mind towards receiving all sorts of feedback and then incorporate what they believe applies to them. In the same time be ready to handle the frustration of “people not getting it”. Just because you have been breathing, living and working blockchain it does not mean the rest of the world stopped. People have their own jobs and industries they work in. Focus on learning as much as you can and apply the lessons to refine your product. Good luck!

You can now apply for StartupYard Batch #8.

  • Robots
  • Artificial Intelligence
  • VR/AR
  • IoT
  • Cryptography
  • Blockchain
Applications Open: Now
Applications Close: June 30th, 2017
Program starts: September 4th, 2017
Program ends: December 1st, 2017
Petya Lipeva, Puzl Coworking

Exclusive Interview: Puzl’s Petya Lipeva on the Bulgarian Tech Space

On April 11-12 2017, StartupYard will be visiting Sofia to meet with Deep Tech startups, and offer two workshops – one on turning an AI idea into a global business, and the other on storytelling for Deep Tech startups.

Before our next official visit, which is to be StartupYard’s third in beautiful Sofia, I talked to Petya Lipeva, Chief Navigator of CowOrKing by Puzl, one of Sofia’s hottest tech startup spaces, about the tech scene in Sofia, how it’s changed in recent years, and what we can expect in the near future from Bulgarian startups. Here is what she had to say:

Hi Petya, first why don’t you tell us a bit about yourself, and your path to becoming Chief Navigator at Puzl?

Hey StartupYard-ers! My name is Petya and I’m the Chief Navigator at Puzl CowOrKing – a coworking space for IT professionals and IT startups in Sofia, Bulgaria. I joined the team a month after they opened the first space.

My background is in PR and marketing for a Bulgarian tech company in the CG industry. For a few years I was traveling the world and I needed to settle down, so I tried to do some freelancing work. However, being a freelancer is quite a lonely experience for a person that is used to working with big crowds.

I was considering relocating to France or Italy when I found out that two guys opened a new shared space in Sofia and they were looking for a person to run the space. I met the team for a lunch and this was the most random job interview that I ever had. It was a couple of days before the start of a big CG conference that I was organizing and my phone was ringing all the time. Meanwhile we were speaking about anything but my role in the team. It’s amazing how you click immediately when you find your people!

Petya Lipeva, Coworking by Puzl

What makes Puzl CowOrKing, aside from any other workspace in Sofia, a special place?

First of all Puzl CowOrKing is the first industry focused coworking space in Sofia. We created the space to help IT companies and professionals to grow and develop together. The amazing industrial design is complemented with different areas to foster efficiency, collaboration, and creativity both for companies and individuals.

We started with one space in October 2015 and a few months later in May 2016 we opened a new floor that we created specially for early-stage startups. In the beginning of April 2017, we’re opening another floor with 10 dedicated offices for small startup companies. The idea is to have different areas so a team could start with some desks in the area for the early stage startups and move across the different zones as the team grows and develops.

Do you have some success stories from your own alumni you’d like to highlight?

Yes, we do have quite a lot of success stories! I’d say that the whole community of 250 professionals is one amazing success story.

We have quite a lot of starting companies that are funded by different funds and accelerators. We have a few examples of individuals who are starting alone and growing a team of 10 people. My best success stories however are the collaboration stories – I love seeing how companies and professionals in the space start working together and find it valuable to exchange experience and resources.

StartupYard is about to make our 4th visit in as many years to Sofia. What would you say have been the most profound changes about the city and the tech ecosystem there in the past decade? What can we expect when we visit next month?

I would say that about 10 years ago in Bulgaria only a few people had heard the word ‘startup’  and the entrepreneurship ecosystem basically didn’t exist. However a decade is quite a long period and the ecosystem is thriving now.

Last year Forbes Magazine named  Sofia  one of the top 10 destinations for starting a business. Only three years after the first venture capital funds Launchub and Eleven started; they have already about 200 start-up companies in their portfolio. Recently we also witnessed one of the largest exits in the region, with a value of 262.5 million USD after acquisition of Telerik by Progress Software.

Quite a lot of organizations are working on organizing entrepreneurship events and trainings and the country is definitely showing a great progress and could show a thriving and interesting tech ecosystem.

What are, in your view, the biggest strengths of Bulgarian tech people, engineers, and thinkers?

I’ve noticed that the engineers in Bulgaria have amazing tech skills – they are talented, dedicated and passionate about their projects. They are real problem-solvers and quite interesting people – there are some quiet ones, loud ones, crazy ones, real inventors, thinkers, and players.

To you, which have been the most interesting and inspiring successes in tech to come out of Sofia or Bulgaria in the last few years?

The most inspiring success to come out of Sofia is Chaos Group – the company that develops the rendering plugin for 3D computer graphics software applications – V-Ray. Chaos Group founder Vladimir Koylazov received an Academy Plaque at the 2017 Academy Awards. The award, presented by the Academy’s Scientific and Technical Awards Committee, recognizes V-Ray’s role in bringing realistic CGI to the big screen.

Another great success is the above mentioned largest exits in the region by Telerik. We have quite a lot of interesting starting tech companies and I’m sure that we’ll see many more great stories in the upcoming years!

What kinds of things do you think we can expect from Bulgarian startups in the near future?

I’d say that we’ll see many exciting products and services coming from the Bulgarian startups and I’m sure that we’ll see many teams growing worldwide. I’m sure that soon enough I’ll be saying proudly “he/she used to work in Puzl CowOrKing”.

Bulgaria is a relatively small economy. Does this force Bulgarian startups to think bigger? Does it have a negative impact on startups looking for their first customers and their first investor?

Yes, Bulgaria is a small economy but it’s a great floor for product testing before going outside the boundaries. The small economy is definitely pushing the startups to grow bigger and to find bigger markets. However, I don’t think it has impact on finding customers and investors, as nowadays we’re all easily connected and because of the thriving ecosystem in the region. It’s easy to access many resources outside the country.

How would you rate the local and state government’s involvement in the tech ecosystem? What are they doing right, and what are they doing wrong?

The local and the state government is not much involved in the tech ecosystem although they are trying a lot. It takes time – the administration in Bulgaria is quite slow in picking up new trends and the tech ecosystem is still something that they don’t completely understand and relate to what’s happening in a starting company. I think the administration needs to attract a new generation of people in order to start helping out the tech ecosystem.

Gustavo Vizcardo, StartupYard

Meet Gustavo Vizcardo, StartupYard’s new Head of Partnerships

It’s our great pleasure to introduce the newest member of the StartupYard team (there are now 5 of us), Gustavo Vizcardo.

Gustavo joins us as Head of Partnerships. He brings over 15 years of corporate experience, most notably as procurement manager for CEE at Coca Cola. Gustavo is also an experienced entrepreneur, and has been a valued mentor at StartupYard since 2015.

Gustavo’s role, which is a new one at StartupYard, is to facilitate bringing innovation thinking from our startups to corporations. The goal is to help corporations to stir innovation while being engaged and learning from our startups, while looking for opportunities and new technologies that will help them to serve their clients, customers and employees in a smarter way. 

StartupYard aims to establish long-term collaborative relationships between corporations and startups.

If you’d like to contact Gustavo about his work with StartupYard, you can reach him at Gustavo@startupyard.cz.

I caught up with Gustavo this week to talk about his new role, and his plans for making StartupYard a key connector between enterprise and startups:

Hi Gustavo! You’ve been with the StartupYard team over a month now. Tell our community a bit about what you’re doing here.

First of all, I consider myself very lucky and privileged to work at StartupYard. My role is to connect startups working on exciting technology, with corporations in a mutually beneficial way. New services and new business models are being born constantly, and corporations are seeking cooperation with agile startups more and more. We’re seeing this across the spectrum, from Fintech to Automotive, to Retail – technological advances are playing a central role in the direction of large companies, and they need the infusion of new ideas and new methodologies from startup companies to move forward.

Part of my job is also to mentor corporations, in the same way that corporates help mentor StartupYard’s startups, on how to get the most out of their relationships with early stage, high tech companies. Corporates need to move at a faster pace, but they are constantly looking for sure footing when it comes to new ideas. StartupYard is a bridge between emerging tech and established business in that respect; we can help show big corporations what they need to focus on and who they should be talking to.

You come originally from Peru, and you’re a UK citizen as well. How did you end up here in Prague?

Well, that’s a combination of a professional and personal reasons. At the beginning of 2013, I was in London working for Coca-Cola,  responsible for marketing procurement in 23 countries in CEE and Southern Europe. Due to my role, the company asked me to relocate to the region.

On the personal side, in the same year I got married to a beautiful Slovak woman, and together we were thinking where will be the best place for us to live. Prague was a natural decision for both of us, and we love it here. At Coke and J&J Consumer, I got an in-depth view of the corporate mindset in a number of countries, and that has really helped me to understand how startups and corporations can begin to work together – even if this is sometimes easier said than done.

I worked with Coca-Cola for a number of years, before leaving to pursue some of my own business ideas, and now to work with StartupYard.

You’re also an entrepreneur. Can you tell us a bit about your previous ventures?

In 2014 I founded ValensGen, a doctor-supervised weight loss program, based on the professional and detailed genetic study of each client. Our ambition was/is to support people to live healthier by using the most advanced technology available.

However, the road has been very, very tough, much more than what we initially anticipated. We’ve made many mistakes which we learned from. Today, the business is somewhat dormant. As we say at StartupYard: the default scenario is failure, so I’m not afraid to admit when things haven’t gone as planned, but learnt from our mistakes and keep working hard.

I still believe that genetics will transform the way how people approach health and healthcare, but the market is really still in the early stages. Consumers are just not aware yet of what genetics tech can do for them, and companies also need to work on ways of using this technology to really deeply benefit people; to make understanding genetics more than a “nice to have” part of a healthy lifestyle. I still want to be part of that.

You spent many years in corporations. Why did you decide to leave corporate life behind and work in startups instead? How does your experience help you in reaching out to corporations now?

Doing business for myself, entrepreneurism, has always been at my core. My father and grandfather were entrepreneurs, and I’ve heard about business since I was a very young. My family ran a successful bakery in Peru. However, by the time I graduated from high school, the economic situation in Peru had become very tough. We had customers, but we had nothing to sell to them. We were experiencing hyper-inflation, and there were shortages of all the raw materials and commodities. People queued up at our door at 6 in the morning to buy bread, but we didn’t even have enough to sell to everyone. It was a very sad time for us, and the country. In the end, the family business closed because the underlying economy couldn’t support it.

Hence, the corporate world was the ONLY option when I first left school. In the last 13 years, I probably had 3 attempts to set-up something for myself, however, I always found reasons to procrastinate. Being in a corporation can give you a safe kind of feeling, and that can make you complacent.

As per the second part of your question, after 15+ years working at large corporations, I understand their complexity and problems, but at the same time, their strengths and opportunities. We have to be empathetic with large enterprises; it doesn’t pay to bash them and see everything they do as inept. If it were, they wouldn’t be around, some of them for a century or more. On the other hand, having gone over my own entrepreneurial experience and as SY mentor, I also have good idea of what the ‘startup’ community can bring in terms of innovation for new/better services.

The fact is that corporations will find ways to survive into the future, and that is not an inherently bad thing. Many people need security, and consumers need some basic consistency in the services they use, and the products they buy. I would not have had a good chance in my life and in my career without the opportunities that an international corporation gave me. They can bring large-scale discipline and efficient processes to people and places who lack them, and need them the most. I still owe much of my thinking to the way I was trained, and I am thankful. Startups are a big part of the future, but not the only part.

What has surprised you so far about working with StartupYard? What have been some of your biggest challenges?

In terms of surprises, I will say there are two fronts: Startups and Investors. I’ve been in contact with our startups from the last cohort since December and I’m impressed about the speed at which they have evolved and improved. This is something I couldn’t imagine before.

As per investors, I’m also surprised about the caliber, experience and expertise of investors in the Czech Republic. They really know their stuff, and work very hard.

My biggest challenge is about how to materialize innovation and technology from our startups toward the corporate world on the sustainable basis.

What can people in corporations do to work with you? What kinds of people would you like to connect with, and how can you help them?

C-Level executives of Czech and International corporations (with operations in Czech Republic), can talk to me about the pain points they are experiencing with technology, and find out how we can align them with startups we invest in and accelerate. I can work with corporations to identify what these pain points are, and begin to show them how working with startups can offer exciting solutions and opportunities.

While we want to work with top management, we also recognize that some corporations are developing internal “Innovation Leads” and other teams which are tasked with bringing more outside tech innovation into the company, and we are happy to support and work with them as well on that mission. Our aim is to help empower these people, by finding ways for them to deliver on their mandate for the company, and break through the typical firewall between a corporation’s internal activities and the outside world.

Komercni Banka, for example, came to us about helping them to shift their internal culture and their strategy towards tech innovation. As part of that effort, we are co-organizing a Fintech Hackathon with them for this month, which promotes their focus on new customer solutions and a better user experience and helping their customers (and their own team) to leverage more emerging technologies. In some ways, we can call that effort a proof of concept for KB – one step in a larger process that involves people at every level of the company.

Big corporations are duly concerned that younger people don’t favor their products, don’t want to work for them, and don’t feel they can be depended on in the way they could as employers and service providers for previous generations. In short, corporations are experiencing many strong challenges ahead, and the only solution is an honest and open approach to innovation, and to the way their employees, the tech world, and their customers are really living and working in today’s world. In a sense this has been a continuous feature of corporate life, but technological progress has accelerated the need for new approaches in recent years.

Rossum, Startupyard

Exclusive Interview: Rossum – AI for Documents

Rossum is a deep-tech startup that joined StartupYard with an understanding of the technology they were developing, but no clear use-case for that technology. The team, a group of PHD candidates in artificial intelligence and machine learning, were exploring applications for machine learning in routine tasks like image categorization.

Through the acceleration process, the Rossum team found opportunities in applying machine learning to corporate accounting, where automation technology has failed to make serious gains in productivity in recent years, due to the sheer complexity and variability of financial documentation. Even invoices alone, of which over 1 billion are sent each day worldwide, are highly resistant to automation due to technical limitations imposed due to historical factors. Rossum began to apply their technology to this problem, and have already made major breakthroughs with the help of a few early key partners.

I sat down this week with Co-Founders Tomas Gogar, and Petr Baudis to talk about Rossum:

Hi Tom, tell us a bit about Rossum. Where did the idea come from?

Tomas Gogar: Hi! The idea for Rossum dates back several years, and it started out as something very different. Our team is a group of PHD candidates who have been studying AI/Machine learning and semantic understanding for a long time.

My Co-Founder, Petr Baudis, is quite well known in AI circles for developing the leading open-source Question Answering AI, something similar to IBM’s own Watson. We actually know that some members of the IBM team periodically test his platform to see how it performs.

Petr also laid the groundwork for Google’s AlphaGo project (the AI that beat a world master in the game Go, many years before it had been predicted that a computer could beat a human). Google cited Petr in their landmark paper in the journal Nature.

The Rossum Team: Petr Baudis (left), and Tomas Gogar (middle), with Tomas Tunys (right)

The Rossum Team: Petr Baudis (left), and Tomas Gogar (middle), with Tomas Tunys (right)

I also have published groundbreaking research on the use of neural nets to parse and understand complex semantics in written text (such as semi-structured documents). It was actually this research that led us to the underlying idea behind Rossum.

Like everybody in this field, we’ve been fascinated by how neural networks and machine learning can be applied to massive volumes of data online. We started with a very popular objective, which is recognition of images and their contents, commonly called computer vision.

When we applied to StartupYard, we had the idea of providing a kind of “AI as a Service,” platform that could be used by researchers or data scientists to apply machine learning to their own problems. One of our innovations was being able to train a neural network on very limited data, which made it very useful for this purpose.

In mentoring though, we quickly discovered that there is actually a huge need for AI that understands and can parse text, in many different formats. We had assumed that problem had been solved by OCR (Optical Character Recognition), but in fact automation based on OCR alone has not really improved in effectiveness in many years. It remains a very hit and miss process.

You’re solving what seems like an unlikely problem- processing invoices. How can AI be applied to that problem?

Yes, it seemed unlikely to us as well! But what we found when we met with mentors from the big 4 accounting firms is that, even in 2017, invoice handling is largely still a manual process. This is despite OCR being around for 25 years already, and electronic invoices existing for over 50 years.

That’s mainly because despite all attempts to standardize and streamline invoicing (including newer techniques like using QR codes to allow machines to read them), it remains a problem that is really too big for any one player to solve. No government or company has been able to get enough others to agree on a single standard, and that has meant, effectively, that the complexity of processing invoices has not changed much for decades. It may actually have gotten worse, thanks to the increasing complexity of the products and services for which we receive invoices, and the increase in the total volume of invoices.

Rossum_Homepage

So just imagine you are an accounting company. You receive thousands of invoices a day. Maybe hundreds of thousands a year. If every invoice takes your accounting people just one minute to process and confirm, that’s hundreds of hours of work that needs to be done. And that is aside from the possibility that you are audited, and have to check all that work for a second time. The human error rate for invoice processing is low, but mistakes are very expensive. Fraud is surprisingly common as well, as bad actors take advantage of the complexities of billing to trick people into paying for non-existent things.

So we began to realize that one answer to this seemingly intractable problem was AI. The big hurdle for automating invoice processing is that no two invoices are ever exactly the same. Getting a machine to recognize one type of invoice, and correctly pull the right information out of it is non-trivial, but certainly possible with existing technology. The problem is that at any time, companies are receiving invoices from many, many parties, a company can change the way it formats invoices, or an invoice can contain a mistake or can be fraudulent.

So that means that no matter how streamlined your process may be, it still requires human-level judgement to confirm that everything is correct. That creates a bottleneck, because human-level judgement takes a long time to apply. People are very good at semantics, but we are also very slow. And you have the influence of many human factors: being tired, misreading a number, forgetting to double check.

Rossum: Human level judgement is slow. And most AI is dumb. Read the exclusive interview: Click To Tweet

AI that can read and understand an invoice at a human level can also be made to do the same work many, many times faster than a human. So if you train a neural network to be able to recognize and work with invoices it has never seen before (just as a human can do), then you can turn hundreds of hours of tedious work into a matter of a few seconds or minutes of computer processing time.

Who would use this technology? Why hasn’t it been developed already?

Well, neural networks are really just starting to be applied to these problems. One of the reasons this hasn’t been done already is that processing power and computer architecture hasn’t been powerful enough to make it possible. The other side of that equation is the data itself. Until recently, much of the data needed to train a neural network didn’t exist in a form that a network could actually handle. Invoices were on paper, or they were “electronic” and thus in a form that could be handled automatically by a hard-wired program.

In the past decade though, the volume of data that we can apply to machine learning has exploded. That’s why AI and machine learning have suddenly become hot topics again.

Rossum_technology

The other issue has been that the specific methodologies for training and checking the accuracy of neural networks have been evolving, and are just starting to become really useful for this kind of work. You can just show a million invoices to a neural network, but getting it to focus on what is important is not something you can just ask for. You have to be able to train the algorithms in ways that help it eliminate useless information and focus on what you want it to focus on.

The process is analogous to the way a baby learns. When a baby is born, its ability to sense information around it is very limited. It can’t see or hear very well, and it can’t process what it does see or hear. Slowly it becomes more able to sense information, and it begins to use that new information to construct an understanding of the world around it. Then comes language: the way that a human mind is able to abstract information and complexity, and imagine new things it has never seen before.

If we are to use this analogy, today neural networks are operating mostly blind, and with little understanding of language to create or understand abstract ideas. As we expose them to more information, we also have to teach them a “language” that they can use to extract something useful from that data. Rossum is a part of that language: we are helping neural networks to understand what we want them to do, and why.

The answer to who would use this technology, is, well, everyone! Human level judgement in understanding documents, even of only a very specific type, would save huge amounts of routine work for humans, who can spend that time doing things that are more natural to them. There is nothing natural for a person about spending their days processing invoices. We can learn it, but we never love to do it.

If you consider how many of these kinds of tasks exist, you realize that we spend massive amounts of time doing things that just don’t bring us anything of value, and in fact waste our time and demoralize us. That is the promise of AI in the near future: this ability to free people from having to deal with things that we just don’t get anything out of, but that just have to be done by someone.

What will be your near-term strategy for bringing Rossum’s technology to market?

As mentioned, we are already in contact with representatives of the major accounting firms. They have the biggest immediate need for Rossum, and they also have the data that Rossum needs to be able to train itself and understand invoices it has never seen before.

In the next few years, we want to have a platform that can understand and work with invoices from literally anywhere in the world, many times faster than a human can, with an error-rate lower than any human. Then the work becomes helping these companies to implement the solution, and find ways for Rossum to interact with other systems so that it can help companies streamline their document handling operations.

It is not much use to an accounting firm for an AI to understand all its invoices, if the AI doesn’t also know how to connect with their other systems, and give the outputs they need to take action. That in itself will be a challenge, and one we anticipate will take some time and development. Still, once you have the ability to process invoices with human or above-human accuracy and speed, then there is a huge incentive on the part of companies to integrate that solution into their systems.

We believe that Rossum will be a must-have for accounting firms in the very near future. And once that value has been clearly demonstrated, we can apply the technology to many other processes that are similar in nature. Auditing, analysis and processing of other documents, etc. Rossum could be a backbone for a suite of intelligent applications that takes care of a wide range of tasks that are complex, and repetitive.

We also want to open up Rossum as an online platform, to allow small and medium sized companies to find it and gain the same value from it. Currently, invoice processing services online come at a heavy cost- over a Euro per invoice in many cases. Rossum can do the same work for a tiny fraction of those costs, and it can do it instantaneously, with a very high degree of certainty.

An automatic platform solution is faster, cheaper, and safer for companies that have confidential information they don’t want others to have access to.

How has your experience been at StartupYard? What surprised you?

Petr Baudis:  We were rather hesitant about joining StartupYard actually, even though we received several personal recommendations from some of the top alumni founders. We were thinking “hey, we have an office and our own good network of contracts, does StartupYard make sense for us?” and we applied at the last minute and very tentatively.  

FullSizeRender 8

Tomas Gogar (right), works with another co-founder at the StartupYard voice workshop

Oh boy, we were in for a real ride when we did decide to join.  Mentoring sessions gave us a much wider scale of perspectives than we could ever gain from our own professional network, and a real and much needed shift of focus from the technical to business.  That we expected a little – but it surprised us how eager the core StartupYard team was to help with their experience and feedback, these few people (including you, Lloyd!) really became an important part of Rossum’s story.  

And most importantly, StartupYard finally gave us the impulse to really focus on one single thing – we were busy people before, but now we had the reason to finally drop all the side projects for good.  We thought the first mentoring month would be the most intense phase, but the pace is only picking up since, and without the “little” pushing by the StartupYard team we would be much more comfortable, getting a good eight hours of sleep a night, but still at the beginning.

Chatler: AI for Conversations at Scale

The past year has seen a boom in chatbots, which have become a buzzword in the tech industry, most particularly with retailers and big brands. StartupYard this year handled dozens of applications for chatbot startups, but despite the buzz, none of these seemed to us to have really discovered the inherent value of automating customer interaction on social media, and in customer care. Chatbots are not a new idea, after all, and much of the recent hype has come thanks to Facebook opening its platform for 3rd party developers, which has spurred renewed interest in new applications for chat.

Facebook’s strategy is bold, and we believe that it may yet yield positive net benefits for end-users and customers, but the chatbot arena is still very immature. And so Janos Szabo gained our attention immediately when we met him and his team during our roadshow, in Budapest last summer. Janos convinced us that the future of chatbots, at least for now, is not in full automation, but in AI integration. He founded Chatler late last year with a team of friends, including strong experience in brand management, to prove that the way forward for chat with big companies is in helping human beings to do what they do best:  be human,

I caught up with Janos this week to talk about his vision for Chatler. Here is our discussion:

Hi Janos, tell us a bit about Chatler. How did you come up with the idea?

I’ve worked a bit with chatbots. I was actually on a team that was creating them. But it quickly became apparent that chatbots aren’t the massive game-changer they’ve been billed as. They aren’t a “fire and forget” sort of thing. They need a lot of care, and a lot of time, and as a result they never end up being as good or as efficient as we hope they will be.

There’s a cycle to AI products in general. It starts with hype: a new way of doing something has its day in the sun, like chatbots, or language translation, and early demonstrations are incredibly promising. But when they’re released into the wild, these things just never work as well as we hope they will. They always have their limitations, and those limitations become apparent relatively fast.

Janos Szabo, CEO and Co-Founder of Chatler

Janos Szabo, CEO and Co-Founder of Chatler

In something closed and strictly defined like Chess, or Go, or even driving a car or landing a rocket on Mars, the rules are clear and the inputs are fairly simple to deal with. But humans are organic, and human conversation is chaotic. Subtlety and context that is easy for a human is incredibly difficult for a machine. I couldn’t land a rocket on Mars, but I can probably handle a customer interaction better than a bot that cost a billion dollars to make. So we have a long way to go.

The problem with chatbots today is the same as it was 20 years ago, when chatbots first were popularized. Some may remember Aimbots, that could answer simple questions according to a hardwired answer-tree. Essentially, modern chatbots work the same way, but pull information from more sources, and understand the intent of questions, perhaps a little better than they used to, when the only thing they really understood were keywords.

Still, 20 plus years, and chatbots can’t do basic things. They can’t judge a person’s reactions to what they say very well. They can’t tell if a person is annoyed, or is making a joke. They can’t think like we do. And they can’t improvise the way a person can.

You wouldn’t trust one to handle your high-value customers, and you might not even trust one to run your Twitter feed. We’ve seen from live experiments from companies like Microsoft that chatbots are still poorly understood. They created a Twitterbot that quickly became an anti-semitic Nazi sympathizer. Of course, it was just doing what it was programmed to do, but that was part of the problem. A chatbot, at the basic level, doesn’t have any sense of morality or of right and wrong. Even backed up by fairly sophisticated AI, it doesn’t have a conscience to guide its actions. It just reacts to inputs.

Now, AI is about learning. We can teach bots how to simulate our own sense of right and wrong. But that’s still on the horizon for modern technology. Today, we still very much need humans to be at the center of communications with other humans. So I started to realize that what we needed to do was, for now, let go of the idea of building bots that can be fully automated.

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We need bots that can learn from us, by showing them how we interact with other people. In time, they can begin to take over tasks that are relatively simple. For example, answering a common question, or accessing an internal system to check a customer’s account information, and other routine tasks that bots should theoretically be very good for.

AI can do a lot of things better than a human can. Particularly routine tasks, but also more complex ones, if there is enough opportunity for the AI to learn them. That’s the assumption that Chatler is built upon. But humans aren’t going away. Until we build an AI that can really feel as we do, there will always be a need for real people.

You’ve actually been selected for StartupYard once before (but didn’t attend), as part of a now defunct startup. Tell us a bit about that experience, and what you learned from it.

Yes, I was one of the founders of ClipDis, which was a tool for message platforms. It was a really catchy product. You could type something in, and it would construct a short video of the sentence using clips from TV and movies. People loved it, and it was fun.

It was a great opportunity for us, but we didn’t fully understand our market, or how to create a real business out of the idea. You have to establish your fundamentals earlier, and spend time on coding later. We were a bit naive, and a bit arrogant, because we had such a cool product, and we thought we could just worry about getting lots of users, and take care of the business part later.

But, especially in Europe, that just isn’t something investors want to be involved with. A hard lesson for us, and something I’ve taken with me to Chatler. I’m still deeply interested in the way people message each other, and how we can understand and enhance our ability to effectively communicate. That has not changed.

What is the market getting wrong about chat, and how does Chatler get it right?

The market right now knows that chat, in some form, is a huge part of the future when it comes not only to customer care, but also to sales and even business development, research, and other fields. So there has been a rush into this space, starting all the way back with Facebook’s acquisition of WhatsApp 4 years ago.

Chatbots seem like an elegant solution to the problem of chatting with your customers at a large scale, but as I’ve noted, they have some really basic limitations. They are good at tasks, but in authentic conversations, they are totally lost. That’s why I see Human/AI collaboration as a key step forward in chat technology. If chat is indeed going to dominate as a future medium for customer communication, then AI is going to play a big part. We just don’t believe it will be the driving force.

Chatler helps big companies and brands make their chat channels more efficient, more responsive, and easier for their customer care and sales agents to use. It does this by learning from the way real people talk to customers, and teaching itself to do routine tasks that real people do. For example, Chatler will quickly learn the best answers to common questions: “What time are you open?” It will then be able to progress to more complex topics: “How do I get to your offices from my home?”

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Chatler will be there suggesting answers for a human to decide upon and use. But eventually, Chatler is going to make that human better at giving answers. Humans make dumb mistakes, like typing a wrong letter, or misreading a map. An AI doesn’t make those kinds of mistakes, so the two working together create a better overall customer experience. Fewer mistakes, faster responses, and better information.

There are a few paths we can take from there. We can more fully develop a recommendation engine that can be applied horizontally to different modes of communication, and/or, we can integrate Chatler more deeply with a company’s operations, enabling it to help a chat agent to accomplish tasks that would take a person a lot of time. Things like looking through databases to find one particular item, or checking multiple sources for one key piece of information. An AI can do in a moment what it can take a person hours to do on their own.

For example, an AI could search your entire communication history with a company instantly, and find out exactly what problems you have had in the past, while a human would take a long time to find and understand all that information. We think humans should be left to do what they are best at- which is caring about other people.

Humans have emotional intelligence. And machines don’t. Certainly not yet, anyway. So the goal shouldn’t be to fake emotional experiences, but to enhance a human’s ability to focus on what they’re best at.

Humans should focus on what they are best at: emotional intelligence. @ChatlerAI Click To Tweet

Why are big brands so interested in moving their customer care operations to a chat format?

A few reasons. FIrst of all, chat is where people are now, particularly younger people. People under 30 now rarely talk on the phone, and school-aged kids today essentially never do, unless forced to. They now see voice-calling as invasive. Some people don’t answer voice calls anymore, directing people to message them instead.

Messaging has become a very visual and creative medium thanks to innovations from Snap, Facebook, and others. It has become a prefered way of communicating between friends and family, and even with some businesses. It’s convenient, and flexible, not requiring two people to pay complete attention to a conversation at one time, and creating an easy record of what’s been said.

A messenger code. Scan it to talk to Chatler.

A Facebook messenger code. Scan it to talk to Chatler.

And for those who remember the early days of ubiquitous mobile phones, chat is more private, and it is also less intrusive to people around you.

Secondly, it’s cheap. This is partly why chat became so popular to begin with, because sending electronic messages uses less data or “calling minutes” than making a call or using VOIP. A customer service person can also service multiple inquiries at once using chat- something that a voice-call center can simply not do. That means that fewer overall people are needed, because the attention of a chat agent is more divisible.

It’s much more important to have more agents available when there are a lot of customers contacting you. And it’s much simpler technologically- without the need for expensive equipment, phone switches, and complex phone-trees and recording equipment.

There is a universe of Customer Relationship Management (CRM) tools and platforms out there. How does Chatler fit into the broader market for these products?

Chatler is focused on chat-based CRM. It will take the form of an end-user solution, but we also plan to offer it as an API for existing CRM providers. That way, if a company has invested deeply in a system that closely matches their needs, Chatler will be easy to integrate in order to make that system more effective and efficient.

Chatler is data driven. Many CRM systems, even those designed for chat, are driven mainly by solutions to logistical issues. We don’t plan to disrupt that, and we don’t pretend to be able to completely replace existing platforms. Instead, we’ll bring a data focus that will help companies in any stage of their chat development. In many cases, our aim is for Chatler shorten a 3-step process into a one-click process, or a 10 step process into a 3 step one, Moreover, Chatler will learn continuously, meaning that what it can’t do today, it can learn to do tomorrow.

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Chatler understands, customer interactions,and recommends effective answers and solutions.

For companies that have never used chat, they can start with Chatler. For companies that are deeply invested in chat already, even better. Chatler will seamlessly enter the flow of existing systems, and save chat agents time and stress throughout the day.

You’ve recently worked on a set of trials with real brands. What did you learn from this experience?

Well, I will be diplomatic and not describe the processes that we’ve observed. We can say that some of them are archaic. Copy paste and spreadsheets are not uncommon. In many ways, the problem is typically that big companies haven’t taken chat seriously from the beginning, and now demand has seriously outweighed their ability to leverage chat. This keeps many brands from even using chat, and it keeps others from using it effectively, or investing in it further.  

Companies are just coming around to the reality that chat isn’t going away, and that it will have some fundamental effects on the way they do business. But that’s just starting. As they did when social media first appeared and changed the way businesses communicate, big companies are constantly weighing the risk and the reward of diving into a new form of communication.

That has helped us to understand what companies need from us. And often what they need is someone to tell them that there is a place to start- a way to make chat an organic part of your business, just as telephones became a part of business a century ago, and the internet became a part of it 30 years ago.

How do you see Chatler growing within the next year? Who are the obvious first customers?

As a standalone platform, SMEs can use Chatler as their primary solution for chat. It will always be better than a native chat platform, because it will be dedicated to learning exactly how your business, and only your business runs, and what kinds of things you communicate, and how you do it. This will extend to mobile as well, as more and more, customers expect to be services on mobile chat.

Large enterprises will integrate Chatler with their existing CRM platforms, and for that we’ll need a global sales team, and a richer, fuller analytics product that helps companies to understand the value that chat is bringing them, and gain actionable insights on their whole chat-oriented customer care operation.

How do you think Chatler will play a role in the further future, 3-5 years from now?

Eventually, consumers will come to expect a chat experience from businesses that mirrors the experience we currently have of the web. Chat will be highly automated, and “explorable,” working together with the customer to solve their needs and find new opportunities for them.

We won’t get to that state by building chatbots. No amount of planning can really tell you how people will use chat. Instead, it will be based on an accumulation of experience, reflected in the complexity of the machine learning algorithms behind Chatler. Over time, Chatler’s AI will become adept at learning about a new company, and finding ways to help take over tasks that it can automate, and interactions that it can handle on its own, then only referring to humans when it is unsure of how to proceed.

This has deeper implications than just making businesses better at chat. Websites and social media both also transformed the activities that businesses actually engage in. It affects the products they create, and the way they do business. Chat has that same potential. The data and experience that Chatler’s AI will gain from conversing with real people will translate to actionable business data, helping companies make better decisions with products, services, customer relations, and more.

Chat will become an opportunity, rather than a liability.

Tell us a bit about your team. How did you all start working together?

We know each other from our previous startup projects, years spent at multinational companies,  agencies, and several meetups.

András Reder has 11 years of experience at Coca-Cola,  leading cross functional teams in a matrix organization. He launched over 17 products/brands into international markets with Coke. Having seen the industry from the inside, András wanted to challenge himself in new projects where A multinational background doesn’t necessarily mean success. He brings the business oriented mindset into our team and makes sure that we all line up from operational POV. 

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The chatler team: Andras, Andris, and Janos

Andris is a freshly graduated coder and bot enthusiast. He organizes the Chatbot meetup in Budapest, supported by Microsoft Hungary. We met at one of his meetups and we immediately jumped into a passionate discussion about chatbots and the future of chat communication. It was an obvious fit for the team. Beyond coding he is also contributing heavily to conversational UX related topics.

With Gábor, Bence and János, we created one of the first chatbots for KIK Messenger’s global bot shop launch (other launch partners were Vine, H&M, WeatherApp). This was the time we started to experiment with recommendation engines, and we realized that even the best algorithm is useless if it doesn’t starts with a clearly defined use/business case.

You’ve known about StartupYard a long time. How has the experience been now that you’ve finally joined us for acceleration?

First I wanted to stay that I should have gone to Startupyard with my previous project. But now I feel lucky that we joined with this project. Having learned the lesson the hard way helps me to appreciate and value the feedback even more. Maybe I would have been more stubborn without  that experience behind me.

The Chatler team during mentoring.

The Chatler team during mentoring.

StartupYard really helped us explore many possible futures, and grow confidence in some of our ideas, while letting others go for now. Instead of sitting in classrooms we were pushed to go out to the jungle and meet possible clients, and investors. This helped us to shape and sharpen our vision through real life feedback. I’m very excited about the progress we’ve made, and where we’re going.