Goderash is the audit layer for regulated AI agents. One decorator wraps any tool call into a SHA-256 hash-chained event — and ships SOC 2, HIPAA, FFIEC, FINRA, and SEC 17a-4 evidence packs an auditor can verify themselves. Apache 2.0. We built this for an in-app financial AI assistant.
This is the kind of infrastructure AI systems actually need. The combination of hash-chained auditability, compliance evidence generation, and verifiable execution history solves a massive trust gap for regulated AI agents. Very strong direction for financial and enterprise AI.
What needs improvement
Very strong concept and highly relevant for regulated AI systems. One thing that could make it even more compelling is deeper support for real-time reconciliation, immutable external anchoring (e.g. blockchain/WORM storage), and standardized audit replay tooling for investigators and regulators. A visual trace explorer for agent decisions and tool execution paths would also be extremely valuable for enterprise adoption.
vs Alternatives
Really impressive work. Most AI tooling focuses on capabilities, but auditability, compliance, and deterministic traceability are what will unlock real adoption in banking, healthcare, and regulated environments. Goderash feels like a critical missing layer.
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