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mrm-ai-detector

PyPIInfrastructure

No liveness check has reached it yet; it is registered on GitHub and PyPI and has been in the index since 11 Oct 2026. How this is checked

mrm-ai-detector is an MIT-licensed Python package for detecting AI-generated content in model risk management documentation. It targets validation reports, model documentation, and MRM policies used by risk and compliance teams.

Inferred · not functionally tested

Open SourceMITCLISelf-hosted
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Overview

6 features

Purpose: Identifying AI-generated text in model risk management and validation documentation.

Inferred · not functionally tested

Audience: model risk management professionals and compliance teams

Inferred · not functionally tested

Functions: data_extraction

Inferred · not functionally tested

Interfaces: API: unknown · MCP: unknown · CLI: indicated (inferred, not tested) · Self-hosting: indicated (inferred, not tested)

Recorded constraints: pricing: open_source · license: MIT · platforms: CLI · deployment: cli, self_hosted

Constraint provenance is unknown; confirm requirements with the publisher.

Record sources: pypi.org · github.com. These links do not verify the individual claims.

mrm-ai-detector sits in PulseGate's AI security & guardrails category. Inferred · not functionally tested: It focuses on identifying AI-generated text in model risk management and validation documentation. Inferred · not functionally tested: mrm-ai-detector is an open-source project aimed at model risk management professionals and compliance teams. Basis unknown · not verified: mrm-ai-detector is open source under the MIT license. Basis unknown · not verified: mrm-ai-detector is available on the command line, and it can be self-hosted.

It is developed by Anirudh Jayaraman, and it first shipped in 2026. The project is developed in the open on GitHub with 2 commits in the last 90 days. Inferred · not functionally tested: Among its 6 catalogued features are AI content detection, document analysis, and model risk focus.

Summary written by a language model from the project’s public pages.

Tasks: Inferred · not functionally tested

  • AI content detection
  • Document analysis
  • Model risk focus
  • Validation report support
  • Policy analysis
  • Python package

Topics: Inferred · not functionally tested

Tags
ai-content-detectionmodel-risk-managementmodel-validationregulatory-compliance
AI capabilities
Text
Inference: Local

JSON profile · Text profile · Access guide

Built with & integrations

Written with
Claude Code
Runs on
CLISelf-hosted
Written with — evidence
Claude Code
commit afb726b7b23c · since Oct 2026

Trust & compliance

License
MIT
Public signals
HTTPSOpen SourceFree tierGitHubActive maintenance

Indexing history

1

What PulseGate has recorded for this listing

  1. Indexed11 Oct · 02:15 UTC
    mrm-ai-detector seen via PyPI Bulk Enumerator
    Source: PyPI Bulk Enumerator · Open

Frequently asked questions about mrm-ai-detector

What is mrm-ai-detector?
Inferred · not functionally tested: Mrm-ai-detector focuses on identifying AI-generated text in model risk management and validation documentation. It is catalogued under AI security & guardrails on PulseGate.
Who is mrm-ai-detector for?
Inferred · not functionally tested: mrm-ai-detector is an open-source project built for model risk management professionals and compliance teams.
Is mrm-ai-detector free?
Basis unknown · not verified: Yes — mrm-ai-detector is open source under the MIT license and free to use.
What platforms does mrm-ai-detector run on?
Basis unknown · not verified: mrm-ai-detector runs on the command line. It can also be self-hosted.
Is mrm-ai-detector still maintained?
The GitHub repository shows 2 commits in the last 90 days.
What projects are similar to mrm-ai-detector?
Similar projects tracked by PulseGate include Compliance Colleague, StackWeaver, and ekbasis.Compliance ColleagueStackWeaverekbasis
Who makes mrm-ai-detector?
mrm-ai-detector is developed by Anirudh Jayaraman.
How long has mrm-ai-detector been around?
mrm-ai-detector first shipped in 2026.

Also in AI security & guardrails

Same category — not a similarity match