SI-Driven QA
Break it in staging, not in production.
A silent model regression reaches your customers, and your brand, before it reaches your dashboard. We build the eval suites, adversarial red-teaming, and drift monitoring that catch failures in staging, protecting both revenue and reputation.
01 · QA capabilities
Six QA disciplines.
Traditional QA catches code bugs. SI QA catches model regressions, safety failures, and retrieval drift. We cover both with the same rigour.
01 · Discipline
LLM Eval Suites
Custom evaluation harnesses measuring accuracy, hallucination rate, factual consistency, and toxicity on your specific domain and queries, not generic benchmarks.
02 · Discipline
Regression Testing
CI-integrated test suites that run on every model version change. A regression in eval score blocks the deploy, protecting users automatically.
03 · Discipline
Red-Teaming
Adversarial prompt testing to find injection vulnerabilities, jailbreak paths, and safety failures before they reach production or a press story.
04 · Discipline
RAG Quality Audits
Context relevance, faithfulness, and answer completeness testing across your retrieval pipeline. We find where your RAG system hallucinates and fix it.
05 · Discipline
Drift Monitoring
Statistical monitoring of live model outputs against your eval baseline. Automated alerts when output quality drifts, before users notice.
06 · Discipline
Load & Latency Testing
Throughput and P95/P99 latency testing under realistic production load. We find the breaking point before your users do.