Question 1

What does your red-teaming cover?

Accepted Answer

Adversarial prompt and jailbreak discovery, hallucination and factuality evaluation, content moderation and policy testing, and model evaluation against real-world risk. The work targets the failure modes that matter for your deployment rather than a generic checklist.

Question 2

Can you evaluate multilingual safety?

Accepted Answer

Yes. Native, in-region teams probe safety and policy failures in the languages your users actually use, which surfaces harms that English-only red-teaming misses. Many jailbreaks and unsafe behaviors only appear in a specific language or cultural context, so native testers are essential to catch them.

Question 3

Do you provide structured findings?

Accepted Answer

Findings come as structured, reproducible reports with severity, category, and step-by-step reproduction, so your team can triage and fix rather than guess. Reproducibility means an engineer can re-run a finding and confirm the fix, closing the loop between testing and remediation.

Question 4

What is AI red-teaming?

Accepted Answer

AI red-teaming is structured adversarial testing that deliberately tries to make a model behave unsafely, produce false or harmful content, or violate policy, in order to find weaknesses before real users do. It complements automated evaluation by using human creativity to discover failure modes that benchmarks do not anticipate.

Question 5

Can you test against our specific content policy?

Accepted Answer

Yes. Corpshore red-teams against your written policy and risk taxonomy, mapping each finding to the policy clause it violates. That makes the results directly actionable for compliance and product teams and produces evidence you can use in safety documentation.

Question 6

How do you evaluate hallucination and factuality?

Accepted Answer

Reviewers probe the model with fact-sensitive and adversarial prompts, then score outputs for factual accuracy and grounding against reliable references. The result is a measured view of where and how often the model fabricates, categorized so you can prioritize the highest-risk domains.

Question 7

How large is the red-team and how fast can it run?

Accepted Answer

Red-team pods scale to the scope and risk of your model, and native-language coverage is added for the markets you serve. Share your model access, policy, and priority risk areas, and Corpshore returns an indicative team size, coverage plan, and timeline before testing begins.

Red-Teaming & Evaluation

Scoped, staffed, and QA-gated

Every unit passes a three-tier QA cascade

Annotator + peer review

Expert QA lead

Programmatic + consensus

Red-Teaming & Evaluation, answered

Ready to scope a pilot?