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The Forecasting CompanyNew foundation models for time series

The Forecasting Company builds planning systems based on our in-house foundation models for time series. We are starting with forecasting problems for logistics.

2024-07-26
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More About The Forecasting Company

The Forecasting Company: Predict Any Time Series with Ease

Introduction

The Forecasting Company offers a groundbreaking foundation model designed to predict any time series with unparalleled accuracy. Upload your historical data and receive precise forecasts instantly, without the need for extensive training.

Key Features

  • Instant Forecasts: Upload historical data and get accurate predictions immediately.
  • Leverage More Information: Enhance forecasts with additional variables like weather, holidays, and events.
  • Enterprise Solutions: Collaborate with our data science team to build enterprise-ready products.
  • Versatile Use Cases: Predict demand, ETAs, volume spikes, and maintenance needs.
  • User-Friendly Interface: Experiment with our system, Navi, using example datasets or your own data.

Use Cases

  • Demand Forecasting: Ensure your shelves are always stocked with highly granular predictive forecasts.
  • Precise ETAs: Improve logistics and delivery times with accurate estimated time of arrivals.
  • Volume Spikes: Anticipate and manage sudden increases in demand or traffic.
  • Maintenance Needs: Predict and schedule maintenance to avoid unexpected downtimes.

Pricing

Our pricing model is tailored to meet the needs of various businesses. Contact us to discuss a plan that fits your specific requirements and budget.

Teams

Geoff NĂ©giar

Geoff has built forecasting systems at Amazon.com, Bloomberg LP, and Shift Technology, and has conducted ML research at Google Brain. He holds a PhD from UC Berkeley's BAIR.

Joachim Fainberg

Joachim has served as a VP with JP Morgan's ML team and has contributed to startups as an ML lead and algorithm engineer. He holds a PhD in machine learning and speech processing from the University of Edinburgh.