The Forecasting Company builds planning systems based on our in-house foundation models for time series. We are starting with demand forecasting for large retailers.
We build foundation models for time series.
Title: The Forecasting Company: Foundation models for time series | Y Combinator

URL Source: 

Markdown Content:


### Foundation models for time series

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



The Forecasting Company

Founded:2024

Team Size:2

Location:Paris, France

### 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

[### The Forecasting Company: Foundation models for time series](

**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)](

### Ask

*   If you have forecasting problems in-house, or know of someone who does, **please reach out - we’d love to help!**
*   **Try our sandbox model** on [ and let us know what you think  
    [founders@theforecastingcompany.com](mailto:founders@theforecastingcompany.com)

### YC S24 Application Video
