veritas-ml
veritas-ml is an open-source command-line tool that enables machine learning practitioners to detect bias and ensure ethics compliance in their models. It provides automated evaluation and reporting features to help maintain fairness and transparency in AI systems.
Overview
4 featuresIn the AI security & guardrails space, veritas-ml takes a focused approach. It focuses on detecting and mitigating bias in AI models to ensure ethical compliance. veritas-ml is an open-source project aimed at machine learning practitioners. veritas-ml is open source under the MIT license. veritas-ml is available on the web and the command line, and it can be self-hosted.
It is developed by anomalyco, and it first shipped in 2026. Key capabilities include bias detection, ethics compliance, and CLI interface.
Summary written by a language model from the project’s public pages.
- Bias detection
- Ethics compliance
- CLI interface
- Model evaluation
Built with & integrations
Trust & compliance
Indexing history
1What PulseGate has recorded for this listing
Frequently asked questions about veritas-ml
- What does veritas-ml do?
- Veritas-ml focuses on detecting and mitigating bias in AI models to ensure ethical compliance. It is catalogued under AI security & guardrails on PulseGate.
- Who should use veritas-ml?
- veritas-ml is an open-source project built for machine learning practitioners.
- Does veritas-ml have a free plan?
- Yes — veritas-ml is open source under the MIT license and free to use.
- What platforms does veritas-ml run on?
- veritas-ml runs on the web and the command line. It can also be self-hosted.
- Is veritas-ml still maintained?
- Activity appears to have slowed — PulseGate's most recent liveness signals classify this listing as stale.
- What are alternatives to veritas-ml?
- Similar projects tracked by PulseGate include Cerno, AgentGuard, and lemma.id.CernoAgentGuardlemma.id
- Who develops veritas-ml?
- veritas-ml is developed by anomalyco.
- When did veritas-ml launch?
- veritas-ml first shipped in 2026.
Also in AI security & guardrails
Same category — not a similarity match