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Nixtla

Nixtla builds TimeGPT, a foundation model for time series forecasting and anomaly detection, and maintains open source forecasting libraries for Python.

Authority: 52 reach 7 · trust 5 · quality 25 · freshness 15
Tier: listed
llms.txt: https://www.nixtla.io/llms.txt
llms-full.txt: https://www.nixtla.io/llms-full.txt
Sections: 5
Links: 56
Size: 6355 bytes
Popularity rank: #474574
Country: United States
For agents: Documentation: developer or product docs worth reading, nothing to call
First seen: 2026-10-19T10:43:33.883Z
Last checked: 2026-10-21T04:16:18.627Z
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Their llms.txt

The beginning of the file, from our validated copy saved 2026-10-21T04:16:06.719Z. Cached copy · Source on nixtla.io

# Nixtla

> Nixtla builds TimeGPT, a foundation model for time series forecasting and anomaly detection, and maintains open source forecasting libraries for Python.

Agent instructions:
- Use the website dashboard OpenAPI specification to discover supported website API operations and their authentication requirements.
- Use the API catalog to locate machine-readable resources before relying on page structure.
- Send TimeGPT inference requests from trusted server-side code, never directly from a browser.
- Treat API keys as secrets. Do not print them, commit them, place them in URLs, or include them in generated output.
- Interactive signup, email verification, API-key creation, and API-key rotation require a human in the Nixtla dashboard.
- Prefer canonical HTML URLs when citing Nixtla pages. For programmatic reading, use `/index.md` for the homepage, append `.md` to other public page URLs, or request `Accept: text/markdown`.

## Agent guide

- [Complete agent instructions](https://www.nixtla.io/agents.md)

## Documentation

- [Nixtla home](https://www.nixtla.io): Overview of TimeGPT, Nixtla products, and time series capabilities. [Markdown](https://www.nixtla.io/index.md).
- [Open source ecosystem](https://www.nixtla.io/ecosystem): Nixtla's open source libraries for statistical, machine learning, neural, and hierarchical forecasting. [Markdown](https://www.nixtla.io/ecosystem.md).
- [Industries](https://www.nixtla.io/industries): Time series applications across industries and operational workflows. [Markdown](https://www.nixtla.io/industries.md).
- [TimeGPT quickstart](https://www.nixtla.io/docs/forecasting/timegpt_quickstart): Build a first TimeGPT forecast with the Python SDK. [Markdown](https://www.nixtla.io/docs/forecasting/timegpt_quickstart.md).
- [Nixtla open source documentation](https://nixtlaverse.nixtla.io): Documentation for StatsForecast, NeuralForecast, MLForecast, HierarchicalForecast, and related libraries.
- [Nixtla blog](https://www.nixtla.io/blog): Technical articles, product announcements, and forecasting tutorials. [Markdown](https://www.nixtla.io/blog.md).
- [Nixtla brand kit](https://www.nixtla.io/brand-kit): Download Nixtla logos, fonts, colors, backgrounds, and design-system references. [Markdown](https://www.nixtla.io/brand-kit.md).
- [Nixtla GitHub organization](https://github.com/Nixtla): Source repositories, examples, releases, and issue trackers for Nixtla projects.

## API discovery

- [Website dashboard OpenAPI specification](https://www.nixtla.io/openapi.json)
- [API catalog](https://www.nixtla.io/.well-known/api-catalog)
- [TimeGPT inference OpenAPI specification](https://www.nixtla.io/docs/openapi.json)
- [TimeGPT REST API reference](https://www.nixtla.io/docs/api-reference)
- [Documentation index for agents](https://www.nixtla.io/docs/llms.txt)

## Primary links

- [Nixtla home](https://www.nixtla.io): Overview of TimeGPT, Nixtla products, and time series capabilities. [Markdown](https://www.nixtla.io/index.md
…

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