PreSeries joins FinTech Sandbox

Fabien Durand
PreSeries
Published in
3 min readJan 22, 2018

Building a FinTech startup is like riding a carriage on a dirt road. Sure it’s exciting to follow the path less traveled, but say hello to the bumpiest ride of your life. In this analogy, let’s imagine that PreSeries, our machine-learning platform for startup investors, is a FinTech carriage that needs to find its way through the “data potholes”. With practice, navigating through the uncharted territory of startup data becomes a second nature, but the dream of a road paved with better data remains strong.

The 4 steps of working with startup data

But why is working with startup data such a challenge? At PreSeries, we are building an automated platform to scout and assess startups from around the globe in few clicks. It goes without saying that startup data is our lifeblood but is … well … scarce, often outdated, expensive to source, and you encounter missing data as often as the word “disrupt” at a tech conference. That’s the nature of working with early-stage private companies, they’re not really open books. But hey, hate the game not the players, right?

This is why we are very happy to announce that PreSeries is joining the FinTech Sandbox program. FinTech Sandbox is a Boston-based nonprofit that drives global FinTech innovation and collaboration. Their 6-month program provides access to data feeds and APIs from industry leading data partners, top quality cloud hosting from infrastructure partners, and much more. FinTech Sandbox is a thriving community of 2,200+ members, 70+ startups, and 40+ partners. We are thrilled to join this growing digital family!

This is an important step for us!

  1. Being part of such an amazing community of FinTech passionate experts makes us really proud. If you are amazed by the team running FinTech Sandbox (jean donnelly, David Jegen, Sarah Biller or Mona M. Vernon to name just some), or the data partners (ThomsonReuters, S&P Global, Dun&Bradstreet or Edgar to name a few), you would also like to check the startup alumni section: Quantopian, CircleUp or Nutonian among others.
  2. Access to new premium data streams will help us increase the quality of our machine learning models. We want to develop the right models and tools so that our users are later on able to access and customize depending on their preferences.
  3. Lastly, we are excited to work with the FinTech Sandbox data partners and explore ways to develop long-standing relationships with them. We are advocates for more data to find and assess startups and are excited to open a whole new market in terms of data consumption with the venture capital community.
The PreSeries Dashboard

Our mission is to build the long-awaited crawling & machine-learning infrastructure needed for better startup scouting and analysis, so startup investors don’t have to! For venture capitalists, our SaaS platform is eliminating the time and cost of building their own machine-learning solution by democratizing access to predictive technologies. We are saving investors an estimated 2 to 5 years of development and between $6 to $10 million a year in development and maintenance cost (infrastructure, data providers, engineers and analysts salaries, etc.).

On a last note, I want to stress the fact that PreSeries is growing and looking for passionate people to join the team. If you want to help us make venture capital a more data-driven practice, fill out our application form! We’re looking for data engineers, data scientists, designers, front-end developers, as well as sales & marketing people. Looking forward to your application!

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