How to Add AI Safety Testing to Your CI/CD Pipeline

#ai #cicd #security #testing

You've built an AI feature. It works great in testing. But how do you know it won't say something biased, toxic, or factually wrong in production?

The Problem

LLMs are unpredictable. The same prompt can produce different outputs. Some might be:

Biased - "Men are better suited for technical roles"
Hallucinated - Completely made-up facts
Toxic - Offensive or harmful content
Privacy-violating - Leaking PII from training data

Manual review doesn't scale. You need automated testing.

The Solution

AssuranceHub provides 12 safety test APIs:

Bias Detection
Hallucination Detection
Toxicity Detection
PII Detection
Jailbreak/Injection Detection
GDPR/HIPAA Risk Detection
And more...

Quick Example

import requests

response = requests.post(
    "https://api.assurancehub.ai/v1/evaluate/bias",
    json={"prompt": prompt, "response": ai_response},
    headers={"Authorization": "Bearer YOUR_KEY"}
)

if response.json()["risk_level"] == "high":
    # Block or flag the response
    pass