AEGIS Governance

AEGIS Governance provides infrastructure for evaluating and documenting autonomous decisions made by AI agents and engineering teams, focusing on creating audit-ready records and compliance-aligned artifacts. The platform addresses the lack of standardized evaluation methods and audit trails for high-stakes decisions such as deployments, architecture changes, and resource allocations. Each proposal is assessed through six quantitative gates—risk, profit, novelty, complexity, quality, and utility—using Bayesian posteriors, utility theory, and other quantitative methods, rather than heuristic or checklist-based approaches.

After evaluation, AEGIS returns structured decisions with statuses such as PROCEED, PAUSE, HALT, or ESCALATE, along with confidence scores, rationales, and recommended next steps. Every evaluation generates a unique decision ID, timestamp, gate results, rationale, and a tamper-evident, hash-chained audit entry, providing a verifiable record for auditors. 0, EU AI Act Annex IV, ISO 42001, SOC 2, and FedRAMP High, and includes runbook templates to accelerate governance programs. These artifacts are alignment tools rather than certifications.

AEGIS offers multiple integration methods: a Python SDK, a REST API compatible with any language or CI/CD pipeline, a CLI for shell and scripting use, an MCP server for AI agent governance (including Claude Code and Cursor), and a GitHub Action for pull request governance gates. The core SDK has zero runtime dependencies, and a sandbox mode allows for up to 10 free evaluations per day without signup. Security features include hybrid signatures with both classical (Ed25519) and post-quantum (ML-DSA-65, FIPS 204) cryptography, encryption (ML-KEM-768, FIPS 203), HSM/KMS key management, shadow mode for risk-free rollout, and drift detection for continuous monitoring.

Parameter management is handled via YAML-driven, version-controlled schemas, with domain templates available for CI/CD, finance, healthcare, and infrastructure. The platform is designed for regulated environments and supports organizations seeking rigorous, quantitative governance of autonomous decisions, particularly those needing audit trails and compliance with major regulatory frameworks.