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Harnessing AI to Democratize Data Analysis: An Interview with the Founder of ANDREby@jillian-godsil
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3,521 reads

Harnessing AI to Democratize Data Analysis: An Interview with the Founder of ANDRE

by Jillian GodsilMay 20th, 2024
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ANDRE automates survey data analysis into executive reports, requiring minimal user input and no need for statistical knowledge. With a focus on privacy and security, ANDRE addresses the needs of startups and business managers by simplifying complex data tasks. The platform promises to transform data interaction, making insights more accessible and actionable for any business.
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Laurent Rochat is the founder of ANDRE, a data analysis automation engine that supports busy people who need to extract insights from data fast and easily. It uses a mix of analysis heuristics and GenAI in a guided analysis process focused on the stories in the data. ANDRE stands for Analytic Narrative Discovery & Reporting Engine.


In this interview, I extract insights from his time developing the platform.


Interviewer: Thank you for joining us today. It’s always interesting to talk with founders building at the edge. So, you want to democratize data analysis?


Laurent: Thank you for having me, and for the opportunity to talk about my new venture ANDRE. Exactly, we are building a solution that automates survey data analysis. Essentially, it turns raw data into executive reports with minimal user input, allowing anyone to gain valuable insights from their data. ANDRE can be thought of as a synthetic data analyst that is available on demand, 24/7, just for you.


Interviewer: Sounds like a claim! So this product will allow someone like me who has basic knowledge of statistics to conduct survey analysis? Can you explain what it does exactly, and what sets it apart?


Laurent: Well, at least that’s our vision! The entire user experience was designed with simplicity and flexibility as objectives. Essentially, you can click your way through the analysis, focusing on the data stories and the insights rather than looking at the data itself. It doesn’t require any knowledge of statistics, or even any calculus for that matter (laughs). Survey analysis tools are usually quite advanced, and they are for data scientists and analysts, not for casual business people.


First product iterations may still be buggy, but the product will improve over time, and its outputs can save a lot of time already today.


Interviewer: It’s true that it’s quite a different experience compared to using Google Sheets! Who do you think will benefit most from using ANDRE, and how does it address their needs?


Laurent: We will learn our way to product-market fit. For now we are targeting both startups and managers in marketing or HR who need to make quick, informed decisions without getting bogged down by the complexities of data analysis. ANDRE helps them extract and report insights with supporting evidence quickly and easily. With ANDRE they can focus their energy on advancing their objectives rather than on data crunching.


Interviewer: Aren’t people in organizations afraid to give their data to an AI?


Laurent: Yes, of course. This is something we hear consistently. The concern is genuine, and we do everything in our power to handle data safely and responsibly.


First, we pay a great deal of attention to privacy. This is why we use algorithms to remove any PII [personally identifiable information] in the GDPR sense even though our terms forbid using data which contains PII in ANDRE. We also ensure that all personal data is processed and stored with the highest security standards, conducting regular audits and updates to our privacy policies and practices. This not only protects our users but also builds trust in our platform.


And we are also mindful of confidentiality. We never share raw data with any third-party AI that wouldn’t be hosted on our servers in Europe. We deploy AI on metadata and data aggregates, and we scramble the little data that is shared in a way that hinders the ability of an AI provider to reverse-engineer the original data. We handle our user’s data in the most secure way.


Interviewer: That’s reassuring. Now, how did you get the idea to build this new product in the first place?


Laurent: Well, our journey began as far back as 2019. We wanted to streamline our chart-production operations at the insights practice I’ve been running. To optimize our processes, we developed a tool that could automatically extract all combinations of variables to create charts, we then only had to select the ones that were meaningful. This may look like a small improvement at first sight, but moving from a ‘selection approach’, in which each slide has to be imagined and produced, to a ‘deselection approach’, in which the analyst flips through charts and deletes the ones that do not seem useful, had a dramatic impact: we cut down the time we spent on charting by over 60%


Interviewer: Hum, interesting.


Laurent: Yeah absolutely! We started relying on this tool more and more internally, and it became clear that it had the potential to benefit others. When we rolled out successive alfa versions of the product in 2021 and in 2023, we received overwhelmingly positive feedback. We knew it was time to scale up: there was indeed a demand for a SaaS product that would automate data analysis.


Interviewer: I like the name “ANDRE”, it’s like a trend in the AI space to name bots with human names, isn’t it?


Laurent: Yes it’s true. Finding a name was a long and messy process. We wanted the “.ai” domain, and we wanted a name that can say something about what we do. I was searching for different names, using AI to suggest some acronyms that would give a sense of what our product will do, essentially extracting data stories from data and creating full-fledged slide decks from that. When I saw “Analytic Narrative Discovery & Reporting Engine”, it immediately clicked: my grandfather passed away earlier last year and his name was “Andre”. He was a passionate reader of Pascal, the French Mathematician and Philosopher of the 17th Century; I’m 100% sure he would love our project now.


Interviewer: So, there is some soul in it I see. Now, what challenges did you face with the development of ANDRE?


Laurent: Well, a good friend of mine and hugely successful entrepreneur told me recently that “The best CEO is someone who has an equally clear vision of where he wants to be in 6 months, and what to do today to get there”. This phrase is stuck in me now (laugh). In fact, this is the core of the challenge, really, as you are understaffed and must micro-manage everything, and at the same time you need to be sharp on the big picture, the future user, and the business model. And then there are all these other small things from incorporation to HR to sprints that maximize developers’ time ROI.


Building on the bleeding edge means accepting that today’s breakthroughs could be tomorrow’s old news. It adds a sense of urgency that you may not have anywhere else.


Interviewer: Looking ahead, where do you see the future of AI and survey analysis heading?


Laurent: I see a future of interconnected services when it comes to insights, and each of these services will rely heavily on advanced AI (LLMs, RAGs, ..etc.). In a not too far future, agents and humans will work seamlessly together, potentially even without knowing if the other is a human or an AI.


In the short term, we will work on making ANDRE capable of integrating more types of data from more sources, and to analyze more of the data to provide more insights. The current beta is limited, and we will gradually add features to increase the versatility of ANDRE (by integrating time series, and open-text for example).


Interviewer: Can you share a personal story that reflects a moment of realization about the potential impact of ANDRE?


Laurent: One particularly striking moment was during the early testing phase when we had implemented a super naïve prompt to suggest data stories from our pre-processed data with the team. We were able to provide some meaningful suggestions, and we knew then that we would be able to provide analytic capabilities at the narrative level rather than at the numbers level.

We had successfully abstracted away the pain of data analysis; anyone could now think about data stories without the need to look at the actual data.


Interviewer: Thank you for sharing these insights with us today. It's clear ANDRE has the potential to transform the way businesses engage with data.


Laurent: Thank you. We’re just at the beginning, and I'm excited about the future of data science democratization


Interviewer: Where can we find you?


Laurent: You may visit ANDRE (https://andre.ai) and try it for free. We wouldn’t mind your vote on ProductHunt (https://www.producthunt.com/products/andre) on May 19th if you are there! data analysis and helping businesses achieve more with less effort.