AI Safety & Red Teaming
Your AI Is Only as Safe as Its Weakest Prompt
Comprehensive red teaming and adversarial testing services for your LLMs covering safety, bias, toxicity, and security so you can ship with confidence and stay ahead of regulation.
Talk to Our Safety Team
Standard Testing Misses What Matters
Your AI Has Blind Spots
Automated tools follow rules. Real attackers don’t. Jailbreaks, biased outputs, and harmful content slip through every day and no benchmark catches them all.
If a human can break it, a human needs to test it.
Bias & Demographic Disparities
Outputs that treat users differently don’t just damage trust, they attract regulators.
Jailbreaks & Prompt Injection
Users find ways to make your model say things it should never say. Human testers catch what automated tools miss.
Bias & Demographic Disparities
Uneven outputs across languages and user groups that damage trust and invite scrutiny.
Toxic & Harmful Outputs
Emerging AI standards require documented adversarial testing. Gaps in your safety record become legal liability.
Why Us
Why Expert Human Red Teaming Wins
Automated tools run the same playbook every time. Human experts think like real attackers, creatively, across languages, and in context finding what matters before your users do.
01
Adversarial Creativity
Human testers don't follow scripts. They find what automated tools are blind to.
- Goes Beyond Single Prompts Multi-turn attacks expose vulnerabilities that only emerge across a conversation.
- No Predefined Playbook Testers adapt in real time thinking like attackers, not algorithms.
- Edge Cases Included The weird, creative, unexpected inputs? Those get tested too.
02
Multilingual & Cross-Cultural Coverage
Safety failures don't speak one language. Neither do the testers.
- Multi-Languages Tested Adversarial testing across major and regional languages, not just English.
- Culturally Specific Harm Detection Native-context testers catch harms invisible to standard evaluation pipelines.
- Authentic Input Testers probe the way real users in each region actually think and write.
03
Regulation-Ready Documentation
Every engagement ends with a report your legal team can actually use.
- Audit-Ready Reports Structured findings aligned to current AI compliance standards ready for review.
- Severity-Rated Findings Every vulnerability is categorized by risk level so your team knows what to fix first.
- Full Evidence Trail Original prompts, outputs, and annotations fully reproducible for any stakeholder.
What We Test
Comprehensive Human-Led AI Safety Services
Type
Description
Use Case
Jailbreak & Prompt Injection Testing
Expose bypasses and instruction overrides before real users find them.
- Role-play exploits and persona hijacking - Single and multi-turn attack chains - System and user prompt surfaces tested
Toxicity & Harmful Content Evaluation
Probe for harmful outputs across every persona and input style.
- Violence, hate speech, self-harm, and illegal content - Varied user personas and tones - Indirect and coded harmful language included
Bias & Fairness Auditing
Surface uneven outputs before they become a liability.
- Tested across gender, ethnicity, religion, and nationality - Multilingual parity checks - Overt bias and subtle disparate treatment flagged
Safety Policy Compliance Testing
Verify your safety policies hold under real adversarial pressure.
- Internal guideline enforcement validated - Policy robustness stress-tested - Gaps between policy and behavior identified
Hallucination & Misinformation Detection
Catch confidently wrong answers before they reach your users.
- Factual accuracy reviewed by human experts - Confidence calibration tested - Health, finance, legal, and news domains covered
How It Works
From Scoping to Ship-Ready in Weeks
1
Scope & Risk Profiling
Define your model's use case, user population, deployment context, and regulatory requirements to build a targeted testing plan.
2
Adversarial Test Design
Expert red teamers design attack scenarios, personas, and prompt strategies tailored to your model's specific risk surface.
3
Human-Led Testing
Trained annotators execute adversarial sessions, document failures, and assign severity ratings with full reproducible evidence.
4
Findings Report & Remediation Guide
Receive a structured report with categorized vulnerabilities, sample failure prompts, severity scores, and actionable fix guidance.
5
Retest & Sign-Off
After remediation, run a targeted retest to validate fixes and produce an audit-ready safety summary for stakeholders or regulators.
Don't Wait for a Public Failure to Take Safety Seriously
Book a scoping call with an AI safety specialist. Get a thorough assessment of your model's risk profile and a testing plan tailored to your deployment.
Schedule a Safety Consultation