Taming Non-Deterministic AI
Your prompt worked yesterday. Will it work today? We validate prompt robustness, hallucination rates, and resistance to adversarial attacks before you ship.
The Trap
Why "Vibe Checking" is Not Testing
Traditional software testing is binary: Pass or Fail. Generative AI is probabilistic. Spot-checking 50 prompts manually gives you a false sense of security.
A model might behave perfectly 95% of the time, but fail catastrophically on edge cases that manual testers never dream of. You need automated, high-volume evaluation.
Probability & Drift
Models change behaviors with minor updates or temperature shifts.
Infinite Inputs
Unlike UI buttons, text input has infinite variations.
Subtle Failures
Hallucinations often look plausible to non-experts.
Our Methodology
What We Validate
Hallucination Testing
Measuring factual accuracy against ground-truth documents (RAG).
Prompt Injection
Adversarial attacks to bypass safety filters and hijack the model.
Bias & Toxicity
Detecting harmful stereotypes or toxic output in generated text.
Output Consistency
Ensuring the model maintains tone and format across thousands of calls.
Data Leakage
Verifying that training data or PII is not exposed in responses.
Edge Case Stress
Testing with garbled inputs, long contexts, and unexpected languages.
Tangible Deliverables
We don't just give you a "pass/fail". We give you the data to release with confidence.
Testing Artifacts
- Golden Test Dataset: A curated set of 500+ heavy-hitting prompts specific to your domain.
- Vulnerability Report: Detailed breakdown of successful jailbreaks and injection vectors.
Strategic Output
- Release Confidence Score: A quantitative metric (0-100) indicating production readiness.
- Remediation Roadmap: Specific system prompt changes and RAG pipeline fixes.