GenAI Governance Without the Guesswork
Your institution has GenAI use cases in production or in the pipeline — but your governance framework is still catching up. Foundation models behave differently than traditional statistical models. Explainability means something different when outputs are generated text, not a probability score. Third-party model risk takes on new dimensions when you're relying on APIs that update without notice. Most institutions are stuck between overengineering governance and blocking innovation, or underengineering it and hoping regulators don't notice. Ethos gives you purpose-built infrastructure to govern GenAI with the right level of rigor — and adapt as expectations evolve.
AI Use Case Inventory — Catalog every GenAI use case — customer-facing applications, internal productivity tools, code generation, document summarization, decisioning support. No blanket policies that treat a chatbot the same as a credit decisioning model.
Foundation Model Registry — Track every model your institution relies on — vendor, version, known limitations, contractual terms. When a vendor updates their model, you know which use cases are affected before your users discover it.
GenAI-Specific Risk Assessments — Configure assessments for hallucination risk, prompt injection, training data bias, output consistency, data leakage, and explainability gaps. Tailored to use case risk tier, not a one-size-fits-all checklist.
Regulatory Adaptability — Map governance to NIST AI RMF, applicable SR 11-7 guidance, and your internal AI policies. When new supervisory guidance drops, update once and cascade across every use case.
