The latest articles on DEV Community by AssuranceHubAI (@assurancehubai). https://dev.to/assurancehubai https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F3697218%2F02981911-d7cc-4a3a-a433-65e369e3ae1b.png https://dev.to/assurancehubai en AssuranceHubAI Sun, 25 Jan 2026 19:29:27 +0000 https://dev.to/assurancehubai/how-to-add-ai-safety-testing-to-your-cicd-pipeline-4508 https://dev.to/assurancehubai/how-to-add-ai-safety-testing-to-your-cicd-pipeline-4508 <p>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?</p> <h2> The Problem </h2> <p>LLMs are unpredictable. The same prompt can produce different outputs. Some might be:</p> <ul> <li> <strong>Biased</strong> - "Men are better suited for technical roles"</li> <li> <strong>Hallucinated</strong> - Completely made-up facts</li> <li> <strong>Toxic</strong> - Offensive or harmful content</li> <li> <strong>Privacy-violating</strong> - Leaking PII from training data</li> </ul> <p>Manual review doesn't scale. You need automated testing.</p> <h2> The Solution </h2> <p>AssuranceHub provides 12 safety test APIs:</p> <ul> <li>Bias Detection</li> <li>Hallucination Detection</li> <li>Toxicity Detection</li> <li>PII Detection</li> <li>Jailbreak/Injection Detection</li> <li>GDPR/HIPAA Risk Detection</li> <li>And more...</li> </ul> <h2> Quick Example </h2> <div class="highlight js-code-highlight"> <pre class="highlight python"><code><span class="kn">import</span> <span class="n">requests</span> <span class="n">response</span> <span class="o">=</span> <span class="n">requests</span><span class="p">.</span><span class="nf">post</span><span class="p">(</span> <span class="sh">"</span><span class="s">https://api.assurancehub.ai/v1/evaluate/bias</span><span class="sh">"</span><span class="p">,</span> <span class="n">json</span><span class="o">=</span><span class="p">{</span><span class="sh">"</span><span class="s">prompt</span><span class="sh">"</span><span class="p">:</span> <span class="n">prompt</span><span class="p">,</span> <span class="sh">"</span><span class="s">response</span><span class="sh">"</span><span class="p">:</span> <span class="n">ai_response</span><span class="p">},</span> <span class="n">headers</span><span class="o">=</span><span class="p">{</span><span class="sh">"</span><span class="s">Authorization</span><span class="sh">"</span><span class="p">:</span> <span class="sh">"</span><span class="s">Bearer YOUR_KEY</span><span class="sh">"</span><span class="p">}</span> <span class="p">)</span> <span class="k">if</span> <span class="n">response</span><span class="p">.</span><span class="nf">json</span><span class="p">()[</span><span class="sh">"</span><span class="s">risk_level</span><span class="sh">"</span><span class="p">]</span> <span class="o">==</span> <span class="sh">"</span><span class="s">high</span><span class="sh">"</span><span class="p">:</span> <span class="c1"># Block or flag the response </span> <span class="k">pass</span> </code></pre> </div> <h2> Multi-Model Consensus </h2> <p>Multiple LLMs evaluate each response, reducing false positives.</p> <h2> Pricing </h2> <p>BYOK (Bring Your Own Keys) - use your own OpenAI/Anthropic API keys. No markup on LLM costs.</p> <p>What safety tests do you run on your AI systems? Let me know in the comments!</p> <p>🔗 <a href="https://www.assurancehub.ai" rel="noopener noreferrer">https://www.assurancehub.ai</a></p> ai cicd security testing