AI Assurance & Quality Engineering
We build AI systems — so we know exactly where they break
Confidence to ship AI into production. We measure whether your copilots, RAG assistants, agents, and voice bots are accurate, safe, and compliant — then gate that quality in CI and monitor it live. Traditional QA firms lack the AI depth; pure AI consultancies lack the test discipline. We have both, because we build these systems ourselves.
Lo Que Obtienes
A scored quality baseline for every AI surface — hallucination rate, groundedness, refusal rate, latency (p50/p95/p99), and cost per interaction
Your own evaluation harness (eval-as-code) — golden datasets and regression suites that catch degradation whenever a prompt, model version, or vendor changes
Adversarial red-teaming — jailbreak, prompt-injection, PII-leakage, and excessive-agency testing mapped to the OWASP Top 10 for LLM Applications, with before/after guardrail block rates
Multilingual voice QA — Word Error Rate across accents and Hindi–English code-mixing, time-to-first-audio, barge-in recovery, and load testing to thousands of concurrent calls
Audit-ready compliance evidence — EU AI Act Art. 50 transparency, India DPDP consent and notice verification, and ISO/IEC 42001 readiness packs
Entregables
Nuestro Proceso de Compromiso
AI Quality Audit
A 2–3 week diagnostic of your live AI system — a scored baseline, adversarial spot-check, and prioritised remediation roadmap.
Eval Harness Build
We stand up your repeatable evaluation infrastructure — golden datasets and scoring rubrics so quality is measured on every change, not vibes-checked before release.
Specialist Testing
Deep testing where AI actually fails — RAG grounding, agent trajectories and tool-use, red-teaming, and multilingual voice quality.
Gate & Evidence
We wire quality gates into your CI/CD pipeline to block risky deploys, and assemble audit-ready compliance evidence for the EU AI Act, DPDP, and ISO 42001.
Observe & Monitor
Continuous production monitoring — live quality scoring, drift alerting on accuracy decay and cost creep, and a monthly quality report.
Preguntas Frecuentes
Manual and automation testing is commoditised — hundreds of vendors do it. We do the part they can't: measuring whether an AI system is accurate, safe, and compliant, and proving it still is next week. Traditional QA firms have no AI depth; pure AI consultancies have no test discipline. We build AI systems ourselves, so we know exactly where they break.
Hallucination and groundedness rates in RAG assistants, the full execution path of autonomous agents (not just the final answer), tool-call correctness and runaway-cost detection, jailbreak and prompt-injection resistance, PII leakage, and voice-agent accuracy across accents and languages. We turn each of these into a number you can gate a release on.
Yes — this is our sharpest edge. We test Word Error Rate across accents and Hindi–English code-mixing (which breaks most off-the-shelf pipelines), time-to-first-audio, turn latency, barge-in recovery, acoustic robustness on poor mobile lines, and load to thousands of concurrent calls — plus AI-disclosure and consent behaviour for compliance.
We provide readiness, testing, and evidence generation — turning a policy document into testable, evidenced controls: system classification, Art. 50 transparency verification, DPDP consent and notice checks, and ISO/IEC 42001 evidence packs. We are not a certification body and do not provide legal advice — clients engage an accredited certifier and their own counsel. Our work is the pre-audit layer where the readiness gets done.
Completely. The evaluation repo, golden datasets, CI gates, and runbook are handed over as versioned assets you own, with a full team handover. Once your harness exists it protects every future AI release — whether we stay involved or not. We sell method and outcomes and stay tool-agnostic, so you are never locked into a single vendor.
Yes. Pre-release testing is a point-in-time claim; AI systems degrade as data, models, and user behaviour shift. Our observability retainer instruments every interaction, scores sampled production traffic live, and alerts on drift — accuracy decay, hallucination spikes, latency regressions, and cost creep — with a monthly quality report and quarterly review. It plugs straight into our Managed AI Retainers line.
Three tiers. Assure — Starter is a fixed-price AI Quality Audit with a red-team spot-check and roadmap. Assure — Build stands up your eval harness plus one specialist track (RAG, agent, or voice) with CI gates and handover. Assure — Managed is a monthly retainer for observability, drift monitoring, quarterly red-team retests, and compliance-evidence upkeep. The intended path is land small, prove measurably, then convert to the ongoing retainer.
Backed by 60+ projects across 16 industries — see how this expertise has shipped in the wild.
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We build AI systems — so we know exactly where they break