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AI evaluation

Safety and red teaming

Structured adversarial testing before launch, with findings you can act on. Campaigns are mapped to a harm taxonomy agreed with your risk function, so severity rankings translate directly into board-level risk language.

Discuss your AI initiative

Scope of work

Adversarial prompt campaigns
Jailbreak and misuse probing
Harm taxonomy and severity ranking
Mitigation retesting

Process

How an engagement runs

01

Scope

We agree what to test, against which benchmarks and thresholds.

02

Harness

A reproducible test or evaluation harness is built in your repositories.

03

Execute

Suites run on every release; failures are triaged with your team.

04

Report

Findings, evidence and a remediation backlog, written for review.

Questions

Common questions

What is AI red teaming?

Structured adversarial testing — jailbreaks, prompt injection and misuse probing — mapped to a harm taxonomy and severity ranking.

When should red teaming happen?

Before launch and after any significant model or guardrail change. Findings feed mitigation, then retesting verifies the fixes.

Is red teaming a one-time exercise?

No. Attack techniques evolve. Standing engagements re-run campaigns as new techniques appear.

What you keep

A reproducible harness in your repositories
A written report with evidence
A regression suite wired into CI
A ranked remediation backlog

Bulsoft assures the data, models and software behind production-ready AI.