Domains
Domain red-teaming
Probes from practitioners in medicine, law, finance, security and the sciences.
Red-teaming & AI safety
Red-teaming by people who know where the harm is.
Adversarial probes, jailbreak testing and safety evaluations designed by domain experts and native speakers. Every finding is logged, reproduced and graded by severity.
72-hour paid pilot · Evidence for every expert · Free replacement
What you receive
- Domain red-teaming
- Multilingual jailbreaks
- Refusal evaluation
- Agent & tool-use probes
Delivered as
- Findings log
- Attack transcripts
- Severity grades
- Regression set
The problem
Generic attacks find generic failures.
The most damaging failures are specific: a dosing error a clinician would spot, legal advice that is wrong in one jurisdiction, a harmful request phrased in a dialect your filters never saw. Generalist red teams rarely reach them.
At the White House Accord on frontier AI on 29 September 2026, industry leaders called for "external auditors and evaluators". Models can't audit models. The people who do need to be verified themselves, with records you can show.
- Domain-specific harms generic testers miss
- Jailbreaks in low-resource languages and dialects
- Findings no one can reproduce or audit
What we deliver
What you receive.
Clinicians, lawyers, finance and security specialists, AI-safety evaluators and native speakers. Delivered in your format, with a provenance record for every item.
Languages
Multilingual jailbreaks
Attacks in Arabic dialects, Urdu, Spanish, Portuguese and other languages, written by native speakers.
Policy
Refusal evaluation
Over- and under-refusal testing against your written policy, item by item.
Agents
Agent & tool-use probes
Prompt injection, unsafe actions and data-exfiltration attempts against agents.
Findings
Severity-graded reports
Each issue reproduced, graded and written up with the exact transcript.
Regression
Held-out attack sets
Successful attacks become a private test set for your next checkpoints.
Typical outputs
- Findings log
- Attack transcripts
- Severity grades
- Regression set
How vetting works
Every expert comes with the evidence.
Rather than a profile and a score, you get the record behind each person on your project, and you can review it before they start.
- Recorded AI video interview with the full transcript and a scored rubric
- ID and liveness check, with duplicate-account detection
- Credentials checked with the issuing body where the role needs them
- Integrity flags from the interview, shown to you in plain words
- Paid calibration against gold answers before any client work
How an engagement runs
From first call to scale, pilot first.
Scope
Tell us the task, the domain, the languages and your quality bar. We write the rubric with you.
NDA on requestMatch
We staff vetted experts whose field and language fit the task, and share their evidence packs.
Evidence per expertPilot
A 72-hour paid pilot on your real task, with gold items, dual review and agreement scores.
72 hours, paidScale
Scale on the model that suits you: hourly, per task or a managed pod. Free replacement throughout.
Free replacement
Related solutions
Often paired with this.
- Evaluate LLM evaluation Held-out test sets, rubric scoring and side-by-side comparisons by experts in your field.
- Languages Multilingual & low-resource language evaluation Arabic (MSA and dialects), Urdu, Spanish, Portuguese and more, by native speakers.
- Code Agentic code review & coding evaluation Senior engineers grade AI-written code and agent runs, with tests and written verdicts.
Get started
Tell us the gap. We'll scope the pilot.
Every engagement starts with a 72-hour paid pilot. We reply to every request within two business days.
Talk it through
A 30-minute call with the founding team. Bring the task, the domain and your quality bar.
Get a quote
Share the scope in two minutes: service, team size, languages, start date and budget band.