QA teams often face the same problem: duplicate bug reports. Different test cases fail, but the root cause is actually the same. To cut through the noise, I built a Proof of Concept (PoC) using Node.js + OpenRouter AI to automatically cluster similar failures and suggest root causes
Why?
🚫 Less time wasted triaging duplicate bugs
🔍 Faster root cause analysis
🤖 AI-driven clustering & summarization
Tech Stack
Setup
Install dependencies:
npm install node-fetch ml-kmeans dotenv
Add your API key to .env:
OPENROUTER_API_KEY=your_api_key_here
CHAT_MODEL=google/gemma-3n-e2b-it:free
Example snippet:
Example result:
Takeaways
✅ AI reduces noise from duplicate bugs
✅ Saves QA team time during triage
✅ Extensible to native CI/CD logs
This is just a PoC, but it shows how AI can make QA workflows smarter. What do you think of this POC? If you have any suggestions, leave a comment
Or if you want to read the full version, you can click here
More...
Why?
🚫 Less time wasted triaging duplicate bugs
🔍 Faster root cause analysis
🤖 AI-driven clustering & summarization
Tech Stack
- Node.js
- ml-kmeans for clustering
- OpenRouter API (chat model for semantic grouping)
Setup
Install dependencies:
npm install node-fetch ml-kmeans dotenv
Add your API key to .env:
OPENROUTER_API_KEY=your_api_key_here
CHAT_MODEL=google/gemma-3n-e2b-it:free
Example snippet:
Example result:
Takeaways
✅ AI reduces noise from duplicate bugs
✅ Saves QA team time during triage
✅ Extensible to native CI/CD logs
This is just a PoC, but it shows how AI can make QA workflows smarter. What do you think of this POC? If you have any suggestions, leave a comment
Or if you want to read the full version, you can click here
More...