AI Engineering · AI Evaluation

AI Evaluation

Exams for AI: benchmarks, guardrails and sampling before and after launch.

Model-agnostic architecture Private & on-premise ready Human-in-the-loop validation
  AI Agent Execution Architecture
01
Goal DefinitionScoped objective & boundary constraints
02
Task PlanningDynamic decomposition into verified subtasks
03
Knowledge & ContextPermission-aware retrieval over enterprise context
04
Approved ToolsGoverned API endpoints & rate-limited actions
05
Supervised ExecutionControlled system mutations & state updates
Human Approval GateConsequential actions require human confirmation
🔒
Immutable Audit TrailFull traceability from prompt to production state

Exams for AI: benchmarks, guardrails and sampling before and after launch.

Capabilities

What this covers

  • Task benchmarks
  • Guardrail tests
  • Human sampling
  • Regression suites

Use cases

Typical engagements

  • Pre-launch sign-off
  • Change regression
  • Quality sampling

Technology

Tools we reach for

Golden sets, eval harnesses.

Security note

Controlled by default

Identity, least-privilege access and audit trails are engineered into delivery.

Keep exploring

Related pages

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