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Product / UX / Safety & Guardrails

Guardrails AI

Guardrails AI

Framework for input and output guards on LLM applications, with a hub of pre-built validators covering PII, toxicity, prompt injection and output format. It wraps a model call in guards that detect risks and enforce structured output, and runs as a Python library on infrastructure you operate.

The Guardrails AI framework, plus Guardrails Hub, a registry of pre-built validators that combine into input and output guards around a model call. Guardrails-AI-owned validators moved from the private registry to public PyPI in 0.11.0. A separate commercial product sits alongside it. Verified 2026-08-13 via GitHub.

Openness

4 medium confidence
4.0
license
Apache-2.0(OSI) for the framework
source
public
hub
Guardrails Hub validator registry
commercial
hosted/enterprise tier
core-gated
gated

The evidence here does not settle cleanly on the recorded score. Nothing appears to be withheld from the published source: the 661-entry tree of guardrails-ai/guardrails carries a single Apache-2.0 LICENSE and no enterprise directory, the FastAPI server ships as its own public repo with a Dockerfile and a compose file, and the private validator registry that once needed a token is gone - release 0.11.0 moved every Guardrails-AI validator from pypi.guardrailsai.com to public PyPI, the vendor's own migration guide tabulating "Private registry pypi.guardrailsai.com (token required)" against "Public PyPI (no token)". The commercial product beside it, Snowglobe, is a separate simulation product. On that reading the project is ungated and fully open source. What complicates it is the licence rather than the gating: guardrails-ai/guardrails-api, the server that the main package's `guardrails start` launches, is not Apache-2.0 - its LICENSE is adopted from the Elastic License and forbids providing the software to third parties as a hosted or managed service, which is a competition-restricted licence and would place the product at source-available instead. So the evidence points to either end rather than to the middle, depending on which of the two SKUs the product is scored on, and that question is open.

  • https://github.com/guardrails-ai/guardrails recorded 2026-06-29

    Apache-2.0 framework; ~7.1k stars; Guardrails Hub validators; commercial offerings

  • https://api.github.com/repos/guardrails-ai/guardrails/git/trees/main?recursive=1 recorded 2026-08-12

    Full untruncated recursive tree, 661 entries. One license path, the root LICENSE. No ee/, enterprise/, commercial/ or proprietary/ directory, and no license-key module. server_ci/ carries a Dockerfile, fastapi-entry.sh and compose scripts for running the server yourself.

  • https://raw.githubusercontent.com/guardrails-ai/guardrails/main/docs/migration_guides/hub-to-public-pypi.md recorded 2026-08-12

    The token-gated validator registry is gone. "As of Guardrails 0.11.0, Guardrails-AI-owned validators have moved from the private Guardrails registry (pypi.guardrailsai.com, installed via guardrails hub install) to public PyPI." The change table reads "Private registry pypi.guardrailsai.com (token required)" -> "Public PyPI (no token)".

  • https://raw.githubusercontent.com/guardrails-ai/guardrails-api/main/LICENSE recorded 2026-08-12

    The server package is not Apache-2.0. "THE FOLLOWING LICENSE HAS BEEN ADOPTED FROM THE ELSSTIC LICENSE" [sic], with the limitation "You may not provide the software to third parties as a hosted or managed service, where the service provides users with access to any substantial set of the features or functionality of the software." The repo describes itself as the "FastAPI server for hosting Guardrails AI in your own environment" and its 149-entry tree contains no license-key module, so the source is published in full - the restriction is on redistribution as a service, not on what ships.

Adoption

2 low confidence
2.0

7,279 GitHub stars on guardrails-ai/guardrails, which bands at 1K-10K stars, level 2. No download, install or customer figure is published for this product, so stars are the only honest signal and the level is directional; a stars proxy never rises above 3, because a star is not a use.

Capability

4 medium confidence
4.0

Broad validator ecosystem via the Hub; strong on structured-output enforcement in addition to safety checks.

  • https://github.com/guardrails-ai/guardrails recorded 2026-08-13

    README describes Guardrails Hub as 'a collection of pre-built measures of specific types of risks (called validators)' that 'can be combined together into Input and Output Guards that intercept' model calls, and says 'Guardrails help you generate structured data from LLMs'.

Verified 2026-08-12