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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