Lumovra AI is an AI governance evidence platform that captures governance-relevant changes from GitHub and GitLab pull requests, then packages them as independently verifiable Proof Packs for enterprise AI reviews, audits, and regulatory compliance. The platform maps evidence to frameworks including the EU AI Act, NIST AI RMF, and ISO/IEC 42001, and also tracks AI agent tool authorization.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises deploying AI systems struggle to demonstrate governance and compliance to internal reviewers, auditors, and regulators. Evidence of how models, prompts, datasets, and evaluations change over time is scattered across engineering workflowsley, making independent verification difficult and costly.
Solution
Lumovra AI provides an AI governance evidence platform that automatically observes pull requests in GitHub and GitLab, detecting governance-relevant changes to models, prompts, datasets, and evaluations. The platform captures this evidence and turns it into independently verifiable Proof Packs that can be submitted for enterprise AI reviews, audits, procurement, and regulatory requirements. Proof Packs are automatically mapped to major regulatory frameworks, enabling organizations to demonstrate compliance without manual evidence collection. The platform also records AI agent tool authorization evidence, extending oversight to autonomous systems.
Target Audience
Primary customers are enterprise AI teams, compliance officers, and risk managers who need auditable evidence of AI system changes for internal reviews, procurement, and regulatory compliance.
Features
- Automated observation of pull requests in GitHub and GitLab to detect governance-relevant changes
- Proof Pack generation that produces independently verifiable evidence bundles for audits and reviews
- Evidence mapping to the EU AI Act, NIST AI RMF, and ISO/IEC 42001 regulatory frameworks
- AI agent tool authorization evidence capture for tracking approved tool usage
- CI/CD integration for continuous governance evidence collection from engineering workflows