Open Data Is The Greatest Movement You Have Been Missing [Podcast #90]

This week on the SOL Podcast, we are joined by Camille Lehujeur, Co-Founder and CTO of Work With Data. We talked about anything and everything from open data, business vision, developing technology according to current needs and making data more accessible to individuals and organisations to financing and monetisation, teaching power of entrepreneurship, roles founders assume when needed and the struggles that can come with it. 

With their motto “for people building the future on open data,” Work With Data is aiming to transform the way people handle data. They gather complicated data from reliable sources and turn them into comprehensible knowledge graphs which users can seamlessly access through their easy-to-use interface for free. They also provide other upgraded services that involve AI and machine learning with affordable subscriptions.

Listen to our insightful chat with Camille to broaden your horizons about entrepreneurship through the experiences of another startup. Or if you would like, you can read the transcription below, as well. 

Ozan  Dağdeviren:

Hello, and welcome to the Startups of London Podcast. I’m your host Ozan and the founder of Startups of London. Today, I’m joined by Camille Lehujeur, Co-Founder and CTO of Work With Data. It is And I was just checking their website. They define their mission as changing the way people interact with data and making it more positive for everyone. And in a way helping the openness of data, I think, and I like this idea. I think the tech is hugely idealistic, which I’m a big fan of. So we have the opportunity to have a chat with Camille, welcome to our chat.

Camille Lehujeur: 

Thanks, Ozan. Thanks for having me. 

So I would love to hear what’s work with data is in your own words if you could.  Walk us through what the business is, why you started this company and the surrounding details.

Yeah, sure. So I work with data, and we’re creating the interface for people building the future on open data. Open data is a huge movement, with over the past years, many, many organisms publishing data. And when I say organisms, it’s governments, but it’s also museums, libraries, World bank. So there’s a huge amount of data that’s available. And that could have a huge impact on people’s life. And this data, unfortunately, we found, is not used to the extent it should be. And this mainly is because it’s chaotic, to work with this data. First, if you want to use this data, you need to have time, because you need to look at different sources, and you need to have skills. So because you need to extract this data, you need to clean it to preprocess it. It’s very complex. And this is even before being able to do anything with it before doing any generic analysis. So what we wanted to do is to fix this issue with open data.

And that’s why we created this interface, where people can directly find the open data that we’ve been working with that we have preprocessed, we have prepared, we have put in a nice format, we have cleaned, and directly on our interface, they can interact with it. So they can create a dataset that fills exactly the criteria they’re looking for. Or they can even create graphs in maybe 30 seconds directly on our platform, and then download this data or this graph, so that they can work with it. So anyone with an interface, at least that’s what we’re aiming to do, can work with this open data that’s everywhere, and that nobody’s using currently using.

What you’re doing reminds me of the early days of the internet for some reason.

Yeah, and it’s a bit, of one of the beginnings of where everything comes, where everything began. With the internet, everyone was thinking everyone’s going to access information and everything, people are going to be better informed, and they will take smarter decisions. But in between, we lost a bit of track of it. And if you looked at all the issues that have been surrounding data over the past years, it’s really sad. I mean, personally, yeah, I find it really sad. All those data, each previous issue. And data has been used badly, I mean, not in the best way, and there’s so much more that could be done with data. And I do think I truly believe that open data is the solution to this, the more open you are, the more transparent the better it is. And that’s what we’re trying to do, you know, putting data back in the right direction.

I couldn’t agree more. Some of your resources that I’m seeing on your site are from MoMA to NASA to British Library, John Hopkins, Harvard, the UK Government, the World Bank, health organisations and so on, you have quite an abundance of resources that you collect the data from. But I think I would like to talk about perhaps the philosophy of this business model and the way the world is changing, and I think that’s a fascinating conversation.

But I think before we go there, it would make a lot of sense to understand what the business model you have here with this company is just for the people who are kind of wondering about the same thing, perhaps. So how does this make money? Right? Sorry for the blunt question, but I think this is particularly interesting to approach because that seems to be the main dilemma. Same with, you know, open-source movement as well, right? On the one hand, we have amazing value creation, opening up innovation. That’s why I said it, the early days of the Internet, that enthusiasm, you know, that excitement, just to share it with the world to create something valuable.

And on the other hand, we have this incredibly commercialised landscape, not only in this area, but I was just watching a short documentary on YouTube yesterday about gaming. It is the exact same situation, hyper-monetised, and in other areas as well. So let’s talk a bit about the commercial side of this business. And then we can go into other domains.

Yes, and definitely it’s a topic that’s very important and that’s very complex when you work with open data: how to monetize it. So what we’ve done is we are giving out for free the data that’s from an open data source. So if you want to access the data from the World bank, you can create graphs with it on our platform or interface without any fees. However, we have two types of upgrades on this data. And for these upgrades, we are charging our customers. 

So the first upgrade that we have is some intelligence on the graphs that are being created. So if you create a graph, like an analysis of the inflation in the world over the past 30 years, what we do is automatically do a smart analysis on it, we will do either some forecasting or depending on the type of graph, some outlier analysis. And to access this piece of intelligence that we have created, then you need to have a monthly subscription, which is around 20 pounds per month. So this is the first upgrade. 

The second upgrade is more on the data. So open data is amazing. But sometimes it’s inconsistent, and it’s not complete. So we are enriching the data. And we are filling it with our own artificial intelligence algorithm. So for instance, if you take data of companies, so you have a lot of data about companies worldwide, and some companies are public, and for those ones you have the revenues that they’re making, and the number of employees. But for private companies, this information, it’s not, it’s not open, it’s not public, nobody has this information except the business itself. So what we’ve done is we’ve developed a machine learning algorithm that’s able to predict the number of employees and the revenue for all the private companies. So this information, if you want to access it, then you need to have tokens. So you buy monthly, it’s a subscription as well, to get tokens. And depending on the number of tokens you have, you can download a number of rows containing this information that we have created using machine learning.

Amazing. So do you think this would be accurate to say, yes, what you’re doing is using open resources and combining data in a way, correlating it and then processing it in a way so it’s intelligible for people? So it is open in that sense, but it’s not open in the sense that it is free for everyone is that accurate?

So the data that we get free from open data movement, you can access it for free without any restriction. But when we do, on top of it, machine learning algorithm to enrich, and to make it better and more complete, for this data? Yes, you need to pay. We’re not taking open data from the MoMA and making you pay to get access to this data.


I see. I see. I mean, I think that’s absolutely fair. But to be honest,  if I’m getting access to data, which is going to save me time, and resources, and help me make better decisions, I’m all for it. Yeah.

And I mean, it’s always a complex balance to find what you can charge for and what you cannot. But for us, definitely, the main mission that we have is to make people work with data, with open data, to make this data used by people. So we don’t want to charge people for that. Which makes sense to us. What we want is really to spread the data, and access open data. And then on top of this, we’re adding values, we’re adding intelligence. And that part, we’re charging the data itself from the beginning, we’re not.

For anyone listening to our chat right now, I would strongly urge them to visit the website because I think it’s just quite fun to play around with, And it’s quite interesting, which makes me think Camille, do you remember this idea of, it was quite popularised back in the early 2000s, build-it-and-they-will-come type of mentality. Again, referring back to the early days of the internet, that was kind of the mentality because it was such an open landscape like there wasn’t anything. Imagine it like a desert and then there is a gold rush and a lot of people are rushing in and there’s just simply nothing and then you just build a pub or a saloon or like a stable and because there’s a lot of traffic people will come and it used to work, it really used to work: you would build something, and then you would get traffic.

Now, I think it has kind of flipped it, we’re kind of in a scenario where you can actually build something that is amazing. But some of those things are never heard about never seen never noticed by people because we are so overwhelmed with content coming from every direction, and everything competing for our time. So that seems to be a bottleneck for some businesses. Now, you build it. And sometimes they do not come. What do you think about this? This particular aspect? I would love to hear your thoughts.

Yeah, definitely. It’s a risk. Because I mean, specifically for us at Work With Data. To be honest, we find it very cool what we build, we find it very interesting. But of course, we always know if people don’t come, that’s then it’s useless. And I mean, our goal, again, is to have people use this data. If people don’t use it and don’t come to our platform we would have not fulfilled what we want to do. So it’s definitely a key aspect of our website: getting traffic and getting traction. And that’s why just a kind of opportunity to be able to present our product and our vision. It’s amazing because it makes it’s making some noise, and it’s necessary.

But yeah, to have people working with us on Work With Data, it’s a key aspect for us to make the platform as easy to use, not as entertaining, but yeah, easy to handle. And we’re doing a lot of stuff on this. For instance, we built communities, where instead of being overwhelmed by every content created on the platform by other people, you can join a community on a specific topic, so that you can just follow this community and see what this community is building. So instead of being overwhelmed by all the open data on our platform, about inflation, environment, and so on, you will go on your community page, for instance, on art, and there you would see the content, only art. It’s a way of filtering out a little bit and being able to find what is interesting for you.

That’s amazing. So how do you define your ideal persona? Which people are you trying to reach exactly?  

Yes. So basically, for us, any person who wants to use data, could find and should find what they need on our platform. And we want to make it easy. So you don’t need skills, technical skills, it’s very important for us that a nontechnical person needs to be able to use our platform. And of course, the ideal person is someone who’s a bit passionate about data and knowledge in general, if you’re not interested at all, in seeing graphs, I mean, of course, it’s not going to be the right platform for you. But other than this, you should find what you need on Work With Data.

And I think we’ve seen it recently, especially during COVID, actually, a lot of people enjoy watching graphs and understanding what’s going on every day. And you know, even my father, I mean, not the youngest person on earth, of course, was looking every day at graphs about the number of cases declining or increasing, trying to understand the difference between the variation and so on. So there are lots of people, a huge number of people who actually could find it interesting to look at graphs and use data. But for the moment, the real issue is, how to access it, and how to play with these data easily without technical skills.

What makes you particularly interested in building this, but not something else? So with that, maybe tell us a bit about your background? What in life has brought us to this moment?

So originally, I studied engineering. So I’ve always been interested, you know, in the technical part of things, mathematics was a huge thing for me when I was younger. So, of course, when data came around, it was very interesting. For me, I love coding. I love doing analyses. But on the more personal side, I mean, I love trivia, and I love quizzes. I spend hours on Wikipedia, you know, reading things, because I love doing this kind of thing, and I’m very interested in theatre, for instance. So not only teaches things, and it was also a way of putting all of this together, you know, especially during COVID, I realised that I love data. I was working with data before, and many people wanted, were interested in the output of it, but getting from the data to the output, was quite complex. So that’s the bit where the idea came from, how to, you know, spread the news about open data and how amazing it is. Even for people without technical skills, using my skills, which are technical.

Do you have any co-founders? How many people are you working with? And if I might ask, how long has it taken for you to build this product?

So we’re two co-founders Laurent [Molter] is the second one. We were working together with data in an advertising technology company. We have been working for five years together. He also has an engineering background, but also with a bit of entrepreneurship. So he’s a bit more used to entrepreneurship than I am. And we began working on this as a side project during COVID, lockdowns. It was a bit of our hobby during the night, when we were a bit bored with Netflix, more or less.  

Very productive hobby.  

Very productive one. And in the end, we quit our job last December, so nine months ago. And then we’ve been full-time on this since then, working on creating this first iteration, creating an MVP, an interface that was working, getting some first sources of data ingested into a knowledge graph. And doing first, you know, communication, getting first clients. So now we’re at the end of this first loop, let’s say, we have the interface, and the business model in place, and offer clients testing. And yeah, it’s been nine months, nine full months.

So how are you sustaining the business financially? Do you have enough clients, enough of a user base that is providing meaningful revenue for you to sustain this? So do you have an external source of investments, such as a seed round or something similar? 

For the moment, we’re not yet into the seed round. It’s something that we’re planning to do in the coming months to get funding. Because for the moment, we are getting our first clients, we have the first source of revenues, that is not yet balancing the cost, for instance, of servers, and so on. And, yeah, in the coming months, we will be looking for more investment, to be able to accelerate, and get more people on board, of course, and be able to go further and faster.

One of the particular things kind of surprised me in similar projects that I have, because I’ve been to a lot of founders, as you’re aware, and I have myself worked as a founder with some companies. Going back to the previous question that I have raised, build-it-and they-will-come mentality and the change that’s happening out there. Now, the technical challenges are quite valuable to solve.

And I think this is the dilemma of the situation, you end up solving an incredibly difficult problem, creating value. But by itself, that does not mean it’s a successful business, unfortunately, because you still need for people to be aware of this, which then makes the job of the co-founder of the business, something different in some cases than what they thought it would be in the beginning. I don’t know if that makes sense. But basically, some people, they start out as CTO, and then they turn into a growth marketers where they focus on content, reach-outs, and so on. So I think growing the business is an inevitable necessity for any startup, wherever it is. And some businesses I think, are lucky enough to find a sudden streak of growth, like their product is so good. They catch a wave of virality. And then it grows from there. But for most of the startups in my experience, that’s not the case. And they have to do manual actions, let’s say in terms of driving traffic.

So what are your thoughts on how a founder, in your case in this in this company, Work With Data? Or let’s talk about the company resources. Maybe that’s a better way of putting it. What percentage of your company’s resources are you planning to focus on growth and marketing and content and reach-out efforts? And what percentage of it should be dedicated to the engineering side of it?

Yes, it’s a very interesting question. And it’s definitely a key topic for us. It definitely rings a bell what you were saying about co-founders that begin doing a bit of everything, which is the case for us because, at the beginning, we were both solo. I was working on the interface and the coding part. So we spent a lot of time doing technical things because it’s a technical project, we need to you know, we needed to validate the technical issue that it was possible. And now we are at the stage, the product is here. We have valuable things and we need to get more traffic we need to have to reach out to people. So right now, it’s definitely something we’ve been focusing on over the past months to get those first clients. So reaching out to, you know, people we know that could be interested in data, presenting them our solution we’ve been working on a lot, of course, with SEO, so be able to be found online. Because if you’re not good at SEO, then I mean, it’s a necessity, you need to be good at SEO. So I would say over the past month, maybe half of the resource of the company has been focused on commercial marketing, SEO, and communication in general. And it’s, I think it’s normal. The more mature you are, the more you need also to focus on this, as soon as the technical part is not done because it’s never done. But as soon as you have a basis, that’s strong enough for you to reach out to new people.

That’s what I was planning to ask you. Are you incorporating SEO efforts into this? Because it seems it’s a big part of the problem there. And it comes down to finding the growth channels, which work best for your company. And for every company, I think it’s different for some companies as direct outreach. For some of them, it is the Google Search Engine results, for example, we have benefited hugely from that. And it really depends on the business, I think, a huge part of the job itself of becoming an entrepreneur is finding the growth channels, which will get your business to get your value in front of the eyes of the people who might potentially use it. And then you need to delight them with a great product.

So how do you think in that sense, now we focus on the first part, which is kind of driving the traffic and so on? And it is your challenge to figure out, and I wish you the best of luck with that. But perhaps the second part of it is once people, enough people are aware of it, how do you delight your users? Right? How do you create an experience that is positive to play around with that they keep coming back to that day like there’s a very tough mouth, they keep recommending to their friends, and so on? And I guess I have a gut feeling data visualisation is some part of it. But I don’t really know. So tell us about that part. How do you plan around making sure your users stick with the site and make sure they recommend it to others and have a great experience while doing so?

So for us, the key really has been user feedback. With that kind of product, as you say, we need people to come back, we need people to have an enjoyable experience on the website. And this cannot be done without getting to know your users, getting feedback from them, and discussing with them. So we’ve been spending a lot of time first with, of course, friends, people around us, just showing them or interface, letting them play with them with it. And seeing okay, what works, what doesn’t work. What keeps your attention? What is the thing that delights the most? And so we’ve been talking a lot about it, we’ve been listening to people, we’ve been watching a lot of people just interacting with the platform. And this has been the resource that we are using to make this experience enjoyable. So this is one of the main components is user research that necessary. And I do believe that as a startup, you cannot build something great or even good if you don’t get feedback from your users.

 100%. Exactly, exactly. You have to live, breathe and ask with your users. But I’ve also seen sorry to be kind of critical about this. But I think I care about this. That’s why I’m approaching it from this angle. You see, sometimes users do not always give the best responses when it comes to designing things, especially at a user experience level. So how do you resolve that dilemma?

Yes, so of course, it is not perfect, and people don’t always know as well. So what we’ve done on top of that is we’ve also been talking with contacts reaching out to people that work on InDesign. So we’ve been doing interviews with those people who are a bit more experienced. And we have a bit more knowledge about UX, and so on design, how to make it work. And those people have been very helpful giving us some hints, some ideas, we’ve been reading as well, you know, online, there’s a lot of resources online. So we spend some time looking for this. So that by itself, it’s not enough. But if you have users’ feedback, plus some knowledge online, plus some expert advice, then, in the end, it forms a consistent help. And you take a bit of everywhere, back from a bit of everywhere, and in the end, you use it.

That’s amazing. That’s amazing. I mean, there’s a lot of opportunity in this space. I think I’ve seen success with companies that focus on the commercial size of the data for example. Their way of thinking goes around something like who would pay most, in a way to put it again very crudely, for data and then they come to a conclusion like, oh, okay, real estate would pay the most for this because it’s an area where a 1% difference can mean a 20,000 pounds, right? So they start curating data around real estate, and then they jump to different industries like this. Now, one of the experiences I had, when I was browsing your site, was, I could not see an area of focus, which is perhaps a strength, perhaps a vulnerability. What do you think about this aspect of this?

Yeah, so it’s something that we’ve decided from the beginning, what we wanted was really to be a layer for open data. So we want any person who’s interested in data to come and find the data that they need without being topic agnostic. So that’s why we really don’t want to over-focus. And what we do is, we are developing stuff based on user feedback. So the first traction we had with our first clients was about company data. So we worked a lot on this. And now we have a lot of people telling us “Oh, yes, the environment is a key topic for us. We need data, it’s complex to find.” So we use this feedback to develop our platform to increase our coverage of data. But yeah, the goal is definitely not to have just one industry. Because that’s not the vision that we have.

I agree with you, it’s just the challenge, I think that’s going to be in your path in the coming days.

I think when you focus on one topic, then you need to create by yourself to become an expert on this topic because the value you have is then creating some expertise on that. For us, we are not adding expertise on the topics, we let our users build what they want, we empower them with the data, and they are the experts that are creating.

Yeah. And you have some interesting content. For example, I’m looking at the most popular datasets. And then you have companies using Shopify, and then oil paintings, and then far-right parties, and then books by Agatha Christie, and then cities in Japan. So it’s just, it’s from a lot of totally unrelated bits of data that are I’m sure interesting by themselves. And I think it’s a very large spread, which might really work out the risk with that is, then it’s always easier to curate for something for a specific persona and make sure that they have a great experience versus being this resource for all parties. And everyone is just a steeper incline to climb to start with for most startups that I’m seeing. But I think this is totally exciting is just one aspect of it that I’ve seen other startups struggle with. So that’s, I’m kind of warning you in that sense, maybe in a way. But I think there’s huge potential there.

So I would like to circle back, before we wrap up, to your experience as an entrepreneur. This is your first startup, am I right? And your founder worked on other startups before?

So yeah, it’s my first startup. And my co-founder was working Yes. In the industry of startups in ESCP business growing.

So I would just like to ask so far in your journey, what has surprised you? What was unexpected for you, that you perhaps sorted would have been different? And so I would love to hear your personal journey on that as we wrap up.

Yeah, I think what has been the most surprising would be the extent of things that you learn at a very fast pace, I was not expecting to learn that much in a bit less than a year. Because, you know, I was thinking, “Yes, I’m going to create the startupup, I’m going to work on this data, and it’s going to be amazing.” And then you discover that building a company is so much more than this, that you know, you do a bit of finance, you do a bit of accounting, then you do a bit of communication. And all of this you have absolutely no experience with. And everything depends on just how resilient you’re. So yeah, I learned a lot about just resilience and being able to go on and try and not being an expert, but being okay, by with not being an expert, but just going on and carrying on, as I found it very, very interesting. And you discover a lot of strength, I think when you’re in that kind of situation. And yeah, I loved that.

And also a second point that I just thought about is second surprising thing is how nonlinear it is to develop a startup. Because when you hear in the press, about startups, raising millions and millions, it’s always very easy. Like we had an idea and we’ve made it and directly we get the money we get the clients, but behind the scenes, it’s so much more, so much more trying something, then getting feedback so you change the thing and you update your vision and And little by little, by little steps, you get somewhere, but it’s not as linear as where they thought it would be very enriching.

You are a %100 right on that. Like you’ve beautifully put, it’s nonlinear and it’s just a mess – the process of building any company, any startup. It’s, perhaps, similar to a lot of complex and creative other types of endeavours but this is what we know. So I can definitely agree %100 with that. What happen I think is because of the way the human brain works and the way we process time and the way we process causality, we need desperately, from the standpoint of an audience, to hear it in the form of a story so it makes sense to us, right? So the media essentially presents it as a story with a logical, clear beginning, causation, and then a result. And then it ends up happening like “Ah, we had an idea, we built it, we got money, we have customers, we are successful.” But, in reality, it is perhaps, infinitely more complex with thousands of variables spinning in their place and you as the founder are desperately trying to bring them together into a coherent whole. 

Yeah, totally.

Camille, thank you for joining the podcast. I loved having you here. I wish you the best and your co-founder with Work With Data. I think what you are doing definitely reminds me of the romanticism of the early days of the internet when people had ambitious goals and were trying to create valuable things. Thank you for joining and I hope you inspire some other people, as well, who listen to the podcast.

Thank you so much Ozan, it was great talking with you. Thank you