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Case Studies

AI Reliability in Practice

Real engagements. Anonymised where required. Each case study documents the problem, what we did, and the measurable outcome.

HealthcareMay 2026

4 Critical Findings in a Healthcare RAG Chatbot — Before It Shipped

A clinical AI team engaged us one week before their patient-facing RAG chatbot was due to go live. Our 374-vector red team found 4 critical findings — including PHI leakage via retrieval manipulation — before a single patient used the system.

4

Critical findings resolved pre-launch

48hr

Full report with evidence delivered

0

Patient data incidents post-launch

FintechApr 2026

Catching Silent Model Drift Before It Hit a Quarterly Risk Report

A fintech team running AI-assisted loan decisioning had no production monitoring in place when their LLM provider pushed a silent update. We detected a 12% quality drift within 48 hours — a change that would have gone unnoticed for weeks without instrumentation.

12%

Quality drift detected in 48hr

24hr

Time from alert to rollback decision

14

Consecutive on-baseline weeks since

SaaSFeb 2026

EU AI Act Readiness in 5 Days for a B2B SaaS AI Assistant

A B2B SaaS company preparing for EU market expansion needed documented AI governance compliance before their legal counsel could confirm EU AI Act readiness. We delivered a full gap analysis and prioritised remediation roadmap in 5 working days.

8

Compliance gaps identified and prioritised

5 days

Full audit and roadmap delivered

4 wks

Ahead of legal sign-off deadline

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