· Standard
A
llmstxt.info Verzeichnis · Standard
Axiom
Community-Eintrag
llms.txt erreichbar
KI-Impact-Score 100/100 · A
Axiom stellt strukturierte Informationen über eine llms.txt-Datei für KI-Assistenten bereit. Branche: Entwickler-Tools. Die Website axiom.co stellt ihre llms.txt unter https://axiom.co/docs/llms.txt bereit. Der Eintrag besteht seit 21. Januar 2026.
llms.txt-Adresse
https://axiom.co/docs/llms.txt
Gemäß DSGVO Art. 17 kannst du die Löschung deiner Daten beantragen. Rechtsverletzung melden (Art. 16 DSA) →
llms.txt — Aktueller Inhalt
Öffnen ↗
# Axiom documentation
> Axiom is a data platform for ingesting, storing, and querying logs, traces, and other event data. This documentation covers the Axiom Console, sending data, the Axiom Processing Language (APL), and the REST API.
Every page below is served as plain Markdown at the linked `.md` URL. The entire corpus in one file: [llms-full.txt](https://axiom.co/docs/llms-full.txt). A standalone APL language reference: [llms-apl.md](https://axiom.co/docs/llms-apl.md).
## Documentation
- [What is Axiom?](https://axiom.co/docs/introduction.md)
- [Quickstart](https://axiom.co/docs/getting-started.md): Go from zero to confident with Axiom. Learn datasets, queries, virtual fields, monitors, and dashboards in progressive steps.
- [Architecture](https://axiom.co/docs/platform-overview/architecture.md): Technical deep-dive into Axiom’s distributed architecture.
- [Features](https://axiom.co/docs/platform-overview/features.md): Comprehensive overview of Axiom’s components, features, and capabilities across the platform.
- [Manage datasets](https://axiom.co/docs/reference/datasets.md): Learn how to manage datasets in Axiom.
- [Edge deployments](https://axiom.co/docs/reference/edge-deployments.md): This page explains Axiom’s edge deployment architecture and how to control where your event data is stored.
- [Limits](https://axiom.co/docs/reference/limits.md): This reference article explains the pricing-based and system-wide limits and requirements imposed by Axiom.
- [Optimize p
[…gekürzt]