Industries
Four Sectors Where Being Wrong Is Expensive.
We concentrate on regulated and high-consequence software. That focus is why the AI assurance vertical packs exist at all. They were built from domain traps we already had scar tissue on.
Healthcare & Life Sciences
Electronic health records, telehealth, and clinical and diagnostic workflows. Privacy and accuracy requirements leave little room for probabilistic behavior, which makes AI features here the hardest assurance problem we take on.
Representative work: a medical intelligence company's migration to Salesforce, where automation removed the manual testing burden and daily diagnostic throughput rose 40%.
Financial Services & Fintech
Banking applications, payment processing, and trading systems. Regulatory exposure and transaction integrity mean verification has to be evidenced rather than asserted, and the audit trail matters as much as the pass rate.
Where AI is involved, the question is never "is it accurate" but "under which conditions, how often, and what happens at the boundary."
Legal Technology
Document review, contract analysis, research, and citation. This is where retrieval systems fail most visibly. A confidently fabricated citation is worse than no answer, and generic evaluation sets do not catch it.
Our legal pack tests grounding, citation fidelity, and refusal behavior on out-of-corpus questions.
Insurance
Claims processing, underwriting, and policy administration. These are long-running processes with regulated decision points, increasingly automated end to end.
The assurance question is whether the system stays inside its authority when a case is ambiguous, which is exactly what trajectory grading exists to answer.
Also served
Where the Pattern Library Came From.
SaaS and cloud platforms, cybersecurity, eLearning, media streaming, collaboration, retail, and trading. Twenty-five years and 1,000+ engagements across those sectors is the cross-project pattern no single client accumulates alone, and it is the actual product.