Solutions
The gap between a working prototype and a production LLM deployment is almost always an evaluation problem. TestML solves it.
Since 2022, we have evaluated 340+ enterprise LLM pipelines across legal, financial, medical, and insurance verticals. The patterns repeat: teams ship confident benchmarks, then discover in production that accuracy means something different to a claims processor than to an internal QA tool. Latency tolerances vary by 10x between a legal contract review and a customer-facing chatbot. Cost spirals emerge at scale.
Structured evaluation, done before go-live and continuously after, prevents those surprises.
A Single Pipeline Across 20+ Dimensions
Most evaluation tooling measures one or two things well. Accuracy. Or latency. Rarely both, and almost never alongside compliance, cost trajectory, and hallucination rate in the same run.
Our pipeline covers accuracy, safety, latency, cost, regulatory compliance, hallucination rate, instruction-following fidelity, and output consistency. Full-spectrum evidence on every deployment, not the three metrics that happen to be easy to compute.
Aditi Verma, Director of AI at a multinational law firm, put it plainly: domain-specific legal evaluation cut post-deployment review cycles by half. That happens when evaluation criteria are grounded in actual operational and regulatory risk, not generic benchmarks.
Red-Teaming Your Specific Threat Model
Generic adversarial tests miss the vulnerabilities that matter. A prompt injection that succeeds against a customer service bot may do nothing to a legal document summariser. The threat model differs.
David Park, our Head of Evaluation Science, built adversarial test suites for three Fortune 500 LLM rollouts before joining TestML. His team designs red-team scenarios against your specific system: the inputs it receives, the integrations it touches, the regulatory boundaries it must hold.
Median time from environment access to written red-team findings: 72 hours.
Sarah Moran, Head of LLM Platforms at a European investment bank, found the value before go-live. Red-team findings caught three regulatory boundary violations before the system reached customers. The blog covers the evaluation techniques behind those findings in detail.
Evaluation Built for Regulated Industries
Legal, medical, financial, and insurance workflows carry compliance obligations that generic LLM evaluation ignores. GDPR Article 22 restricts automated individual decisions. HIPAA requires auditability of clinical outputs. FCA guidance on AI systems demands documented model governance.
Pre-built evaluation suites for each vertical are grounded in those actual obligations. Legal evaluation covers citation accuracy, contract interpretation risk, and privilege boundaries. Medical evaluation targets diagnostic consistency and documentation accuracy. Financial evaluation runs MiFID II alignment checks alongside standard performance metrics. Insurance evaluation covers claims reasoning, regulatory disclosure accuracy, and underwriting consistency.
Continuous Monitoring After Deployment
Models drift. Input distributions shift. A contract clause written in Q1 reads differently in Q4 because the legal context changed. Performance at 94% accuracy during pre-deployment evaluation can quietly degrade to 81% over six months in production.
Ewa Kowalska, our Lead ML Engineer, designed the drift detection pipeline around that specific failure mode. Automated regression testing runs on a configurable cadence. Alerts surface before degradation becomes a compliance incident or a customer failure.
Tom Rigby, VP of AI Engineering at a global insurance carrier, deployed claims-processing agents across seven markets without a compliance incident. Continuous monitoring was part of that outcome from day one.
Data Residency and Deployment Options
Mission-critical workflows require data to stay where you put it. On-premise deployment options keep proprietary documents, patient records, and financial data inside your perimeter. SOC 2 Type 2 certified processes govern how TestML staff access evaluation infrastructure.
GDPR, HIPAA, and ISO 27001-ready controls are documented and auditable. If your legal team needs a data processing agreement before the first evaluation run, we have a standard form ready.
Book a technical review to see what full-spectrum evaluation looks like against your specific deployment.