AI Governance
Published writings and frameworks on runtime AI governance, computable trust, auditability, model lifecycle oversight, and enterprise risk management.
Computable Trust Architecture
A formal framework for making AI trust computable, enforceable, temporally valid, and auditable at runtime. Introduces the Trust Computation System, Trust Integrity Score, and tamper-evident Trust Certificates.
View White PaperThe Enterprise AI Governance Imperative
A framework for establishing AI governance that balances innovation velocity with auditability, compliance, and enterprise risk. Designed for organizations operating in regulated environments.
COMING SOONModel Lifecycle Oversight in Production
Practical guidance on managing AI models from development through production, including drift detection, performance monitoring, and responsible retirement practices.
COMING SOONGuardrails and Evaluation Design for LLM Systems
Approaches to designing evaluation frameworks and guardrails for large language model deployments, drawing from shadow testing, offline evaluation, and production monitoring patterns.
COMING SOON
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