English

TimeCopilot

Machine Learning 2025-11-10 v3 Artificial Intelligence Human-Computer Interaction

Abstract

We introduce TimeCopilot, the first open-source agentic framework for forecasting that combines multiple Time Series Foundation Models (TSFMs) with Large Language Models (LLMs) through a single unified API. TimeCopilot automates the forecasting pipeline: feature analysis, model selection, cross-validation, and forecast generation, while providing natural language explanations and supporting direct queries about the future. The framework is LLM-agnostic, compatible with both commercial and open-source models, and supports ensembles across diverse forecasting families. Results on the large-scale GIFT-Eval benchmark show that TimeCopilot achieves state-of-the-art probabilistic forecasting performance at low cost. Our framework provides a practical foundation for reproducible, explainable, and accessible agentic forecasting systems.

Keywords

Cite

@article{arxiv.2509.00616,
  title  = {TimeCopilot},
  author = {Azul Garza and Renée Rosillo},
  journal= {arXiv preprint arXiv:2509.00616},
  year   = {2025}
}
R2 v1 2026-07-01T05:13:42.553Z