AI Evaluation
AI evaluation measures quality, safety, and business outcomes before and after deployment — continuous, not a one-time QA pass.
AI evaluation measures quality, safety, and business outcomes before and after deployment — continuous, not a one-time QA pass.
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In regulated enterprise AI
FDEEs maintain eval harnesses tied to regulatory policy. Scores feed model risk forums and trigger remediation when production behaviour drifts.
AI Evaluation is essential for governed production AI — not optional for regulated deployments
Pilots that skip this discipline typically stall at proof-of-concept
Derisk360 implements through accelerators with embedded Forward Deployed Engineers
FDEE-led eval harnesses run before and after production deployment
Related resources
- Agent Evaluation
Agent Evaluation — enterprise AI deployment from Derisk360.
- Eval Harness
What is Eval Harness? An eval harness is automated testing infrastructure that scores AI outputs against business and safety criteria.
- AI Evaluation Framework
AI Evaluation Framework — practical enterprise AI deployment guide from Derisk360.
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Common questions about AI Evaluation
- What is AI Evaluation?
- AI evaluation measures quality, safety, and business outcomes of AI systems before and after deployment.
- Why does AI Evaluation matter for enterprise AI deployment?
- AI Evaluation reduces deployment risk and determines whether agents reach governed production in regulated environments. Without it, pilots stall and compliance teams block go-live.
- How does AI Evaluation relate to the 4-Layer Intelligence Stack?
- AI Evaluation maps to one or more layers — context, decisions, actions, or outcomes — in Derisk360's architecture for production agentic systems.
- How does Derisk360 implement AI Evaluation?
- Through structured AI accelerators and embedded FDEs who implement ai evaluation in your VPC — with evaluation and managed operations built in from day one.
- Is this a software product I can licence?
- No. Derisk360 is a services firm. You engage for production outcomes through accelerators and implementations, not shelfware.