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About skforecast-ai

History

skforecast-ai was born from a simple idea: pair the robust, reproducible time series forecasting of the skforecast engine with the advanced reasoning capabilities of an LLM. What if an assistant could handle the complex decisions around forecasting, such as profiling data, selecting models, and evaluating metrics, while explicitly reasoning through each step? The result is a transparent, two-tier system: a deterministic, rule-based core that generates the exact, runnable script, elevated by an LLM layer that explains the strategic why behind every decision without ever altering the underlying math. The project builds directly on the mature skforecast ecosystem and grows alongside it.

Governance

skforecast-ai is an open-source project maintained by its core development team, with guidance and valuable contributions from the community. We strongly believe in openness, transparency, and collaboration. Everyone is encouraged to participate through issues, discussions, and pull requests on GitHub.

Core Development Team

!linkedin Forecasting Python

Meet the core developers behind skforecast-ai.

Joaquín Amat Rodrigo
Joaquín Amat Rodrigo @JoaquinAmatRodrigo LinkedIn
Javier Escobar Ortiz
Javier Escobar Ortiz @JavierEscobarOrtiz LinkedIn

Contributors

GitHub contributors

View the full list of contributors and their contributions to the project.

Thank you for helping us make skforecast-ai better! 🎉

Get Involved

We value your input! Here are a few ways you can participate:

  • Report bugs and suggest new features on our GitHub Issues page.
  • Contribute to the project by submitting code, adding new features, or improving the documentation.
  • Share your feedback on LinkedIn to help spread the word about skforecast-ai!

Together, we can make time series forecasting accessible to everyone.

Citing skforecast-ai

skforecast-ai is built on top of skforecast. If you use it for a scientific publication, we would appreciate citations to the underlying skforecast software.

DOI

APA

Amat Rodrigo, J., & Escobar Ortiz, J. (2026). skforecast-ai (Version 0.1.0) [Computer software]. https://doi.org/10.5281/zenodo.21338159

BibTeX

@software{skforecast-ai,
  author  = {Amat Rodrigo, Joaquin and Escobar Ortiz, Javier},
  title   = {skforecast-ai},
  version = {0.1.0},
  month   = {7},
  year    = {2026},
  license = {Apache-2.0},
  url     = {https://ai.skforecast.org/},
  doi     = {10.5281/zenodo.21338159}
}

License

License

skforecast-ai software: Apache License 2.0

The underlying skforecast engine is distributed under its own BSD-3-Clause License.