Solution
AI System Validation
Your AI shipped. But does it actually work?
Passing unit tests doesn't mean your AI model delivers the outcome it was built for. AI System Validation is the end-to-end assurance layer that measures model performance, safety, regulatory compliance, and business KPI alignment — before production, and continuously after.
01
18
failure mode classifiers
02
40%
more defects caught pre-prod
03
500+
adversarial scenario templates
04
1,400+
regulatory obligations mapped
The challenge
What makes this hard
- Model passes tests on training data but fails on real user inputs outside training distribution
- Inability to establish performance baselines for model updates
- Regulatory compliance assumed rather than verified
- Safety failures discovered by customers or auditors instead of QA processes
- Undetected model drift until business metrics decline
What we deliver
The Qapitol approach
01
Performance Validation — Model accuracy & KPI benchmarking
Measure model accuracy, relevance, faithfulness, and consistency against versioned ground-truth datasets with full reproducibility. Powered by QAVE.
02
Safety Validation — Adversarial & safety testing
18 failure mode classifiers covering hallucination, unsafe outputs, refusal analysis, and bias measurement across 500+ adversarial templates across 12 risk dimensions. Powered by QAVE.
03
Regulatory Validation — Compliance obligation mapping
Auto-map AI systems against IRDAI, RBI, EU AI Act, DORA, and DPDP obligations with 1,400+ mapped requirements and audit-ready Policy Reasoning Traces. Powered by CHEQ.
04
Regression Validation — Model change impact analysis
Compare model versions across evaluation suites to identify regression in specific user intents, personas, or input types.
05
Integration Validation — End-to-end system & API testing
Validate AI integrations covering API contracts, RAG pipeline accuracy, tool call reliability, and agent chain correctness.
06
Production Monitoring — Continuous post-deployment assurance
Monitor model drift detection, output quality, and automated alerting when AI degradation begins.
Next step
Bring AI System Validation to your stack
Scope it in one call — outcomes defined upfront, free assessment included.