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The Forecasting Company

Foundation models for time series

The Forecasting Company builds planning systems based on our in-house foundation models for time series.

Jobs at The Forecasting Company

Paris, Île-de-France, FR
€80K - €130K EUR
0.50% - 2.00%
3+ years
The Forecasting Company
Founded:2024
Team Size:2
Location:Paris, France
Group Partner:Jared Friedman

Active Founders

Geoffrey Negiar, Founder & CEO

Co-founder and CEO at The Forecasting Company, helping enterprise customers improve their operational decision making. PhD grad from UC Berkeley's BAIR. I spent time with Amazon Forecasting Science in SCOT, Google Brain, and Bloomberg LP where I worked on forecasting, optimization and deep learning research.

Joachim Fainberg, Founder & CTO

PhD in ML for speech and full-stack developer. Interned at Sonos where I built an on-device wake word detector and at Bloomberg building a large ASR system. Worked full-time at JPMorgan in their Machine Learning Center of Excellence in New York, and then at two startups, team lead ML/NLP at Consigli, a prop-tech startup, and sr algorithm engineer and full-stack at Vind AI, a SaaS for designing off-shore wind parks.

Company Launches

tl;dr: The same core technology that led to the LLM explosion can be adapted to build accurate and easy to use time series models. We’re building the enterprise-grade, plug and play forecasting systems of tomorrow. Talk to us if you have forecasting and planning use-cases!


Hi everyone, we’re Geoff and Joachim. We’ve built ML and forecasting systems at Amazon, Google, Bloomberg LP, JP Morgan, and Sonos. We’re The Forecasting Company!

Problem 📉

  • Existing time-series forecasting solutions produce unreliable predictions with sometimes catastrophic results - they have a hard time handling activity spikes like Black Friday.
  • Developing and maintaining useful forecasting and planning models requires large and costly teams of data scientists and domain experts.
  • Data science teams are backlogged, leaving operators waiting for months before a use-case to be put into production.

Solution 📈

  • An easy to use, flexible and accurate forecasting system. No training required!
  • A massive training dataset of time-stamped data from many industries and domains (energy, transportation, etc.).
  • A forecasting model that can leverage user-provided input variables or our own curated data streams.

What we’re forecasting these days

Bacteria levels in the Seine 🦠 🏊‍♂️

Our forecasts show that swimmers lucked out today 🍀!
(Data provided courtesy of the Fluidion Open Data Initiative)

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