Role Kernel
Governance infrastructure letting AI agents safely assume 1,016 professional roles.
The Challenge
Deploying autonomous AI agents across regulated industries required more than a prompt — it required real governance: role-appropriate behavior, risk controls, and compliance enforcement across over a thousand distinct occupational contexts.
The Approach
We architected a three-layer hierarchical system: a Baseline layer of 1,016 O*NET occupations with identity and task governance, a Governance layer of industry-specific overlays (Pharma, Finance, Healthcare, Defense) with tailored risk multipliers, and a Client layer for customer-specific customization. We built an ingestion pipeline processing 412,415 O*NET records — including 56,505 aliases and 297,676 behavioral context records — with automated risk classification driving agent operating modes (STRICT, CAREFUL, NORMAL). Semantic role resolution runs on OpenAI embeddings and Pinecone, with an industry-fork architecture producing specialized child roles with adjusted risk overlays.
Key Capabilities
Tech Stack
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