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auditability

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A neuro-symbolic runtime architecture (DIR) for Responsibility-Oriented Agents (ROA). By decoupling probabilistic LLM reasoning (User Space) from deterministic execution (Kernel Space), it ensures safe, invariant-driven, and auditable AI autonomy.

  • Updated Aug 18, 2026
  • Python
veritas_os

VERITAS OS is an AI agent governance runtime for decision control, policy enforcement, approval workflows, audit trails, and replayable evidence before real-world actions.

  • Updated Sep 1, 2026
  • Python

A long-form article and practical framework for designing machine learning systems that warn instead of decide. Covers regimes vs decimals, levers over labels, reversible alerts, anti-coercion UI patterns, auditability, and the “Warning Card” template, so ML preserves human agency while staying useful under uncertainty.

  • Updated Dec 20, 2025

This project integrates Hyperledger Fabric with machine learning to enhance transparency and trust in data-driven workflows. It outlines a blockchain-based strategy for data traceability, model auditability, and secure ML deployment across consortium networks.

  • Updated May 29, 2025
  • Shell

SMALL (Schema, Manifest, Artifact, Lineage, Lifecycle) is a formal execution state protocol that makes AI-assisted work legible, deterministic, and resumable by separating durable state from ephemeral execution.

  • Updated Apr 29, 2026
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