sktime/tserve

Repository for Timestral, the time-series foundation model by Mistral AI

FoundationForecast: the Python API for Time Series Foundation Models ✨. It supports forecasting, cross-validation, anomaly detection, and exogenous variables for models such as AWS Chronos, Google TimesFM, Mistral Timestral, H2O TimeH2O, Nixtla TimeGPT, etc., under the same API.

TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.

Python time series forecasting assistant built on skforecast: deterministic decisions, the script that ran, an optional LLM that explains them, and an MCP server for AI agents.

An open-weights time-series forecasting foundation model from The Forecasting Company.

Foundation Models for Time Series

Scalable and user friendly neural 🧠 forecasting algorithms.

TimeGPT-2.1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.

TimeCopilot: the Agentic Forecasting Framework. Built on LLMs and Time Series Foundation Models, it lets you forecast, cross-validate, and detect anomalies using multiple foundation models through a single API. From finance and energy to web analytics, TimeCopilot turns natural-language queries into production-ready forecasts.