AI & LLM Engineering
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RAG Evaluation with Ragas & Arize Phoenix
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"Hi Daniel, saw your lack of RAG evaluation metrics—I set up Ragas automated scoring pipelines tracking Faithfulness and Context Relevance on every CI pull request."
Why it works: Cites Ragas, Faithfulness, Context Relevance, and CI pull request gating in under 160 characters.
Full Proven Proposal Cover Letter
Hi Daniel,
Saw your posting regarding blind production deployments of your RAG pipeline without regression testing. I build automated RAG observability and continuous evaluation test harnesses using Ragas and Arize Phoenix.
Here is the evaluation pipeline I will deploy:
1. Construct a golden evaluation dataset with ground truth Q&A pairs from historical user queries.
2. Automate synthetic test generation assessing Faithfulness, Answer Relevance, and Context Recall.
3. Integrate evaluation runs into your GitHub Actions CI/CD to block PRs that degrade retrieval quality.
I can show you a live Phoenix dashboard with trace replays. Would you like a quick walkthrough?
Best,
[Your Name]
Saw your posting regarding blind production deployments of your RAG pipeline without regression testing. I build automated RAG observability and continuous evaluation test harnesses using Ragas and Arize Phoenix.
Here is the evaluation pipeline I will deploy:
1. Construct a golden evaluation dataset with ground truth Q&A pairs from historical user queries.
2. Automate synthetic test generation assessing Faithfulness, Answer Relevance, and Context Recall.
3. Integrate evaluation runs into your GitHub Actions CI/CD to block PRs that degrade retrieval quality.
I can show you a live Phoenix dashboard with trace replays. Would you like a quick walkthrough?
Best,
[Your Name]
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