Stress-testing LLMs for production.
Identifying hallucinations, prompt injections, and edge cases before they reach your customers.
The Problem
Liability
Unchecked LLM outputs are a legal and reputational risk.
Safety
System prompts are easily bypassed without adversarial testing.
Cost
Inefficient prompting and model selection burn margins.
Expertise
10 years in the digital sector, including several years at Instagram/Meta. Extensive experience in LLM Red Teaming and RLHF for leading labs via Scale AI and Remotasks.
I have spent years stressing models for the world's leading AI labs.
# stress-test pipeline adversarial_eval() quality_benchmark() mitigation_report() # output: production-ready
The Audit
A fixed-price, 3-step evaluation process for companies shipping LLM features.
Adversarial Evaluation
Systematic attempts to bypass system prompts, jailbreaking, and identifying data leakage.
Quality Benchmarking
Measuring hallucination rates and accuracy under varied conditions.
Mitigation Report
Actionable fixes for system-prompts and evaluation pipelines to ensure production-readiness.
Certificate on completion
After the audit you receive a certificate documenting that your LLM feature has passed our evaluation—suitable for compliance and stakeholder communication.
Contact
contact@stress-test.netAvailable for short-term audits and fractional AI Ops.
Berlin-Mitte / Remote
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