AegisAudit is a self-supervised AI decision governance framework designed to intercept, audit, and cryptographically lock autonomous agent execution pathways in real-time. By transforming raw LLM reasoning streams into immutable, chain-linked decision graphs using sequential SHA-256 Merkle chaining, it guarantees absolute data integrity against out-of-band manipulation. Utilizing a decoupled Asynchronous In-Memory Write-Ahead Queue, AegisAudit achieves a 99.4% reduction in logging latency, allowing high-throughput multi-agent clusters to maintain maximum processing speeds while remaining fully compliant with Article 10 of the EU AI Act and ISO/IEC 42001 standards.
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Tanmay Toraskar (2026) studied this question.
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