How to optimize chunking strategies and retrieval recall for AI agents

How to optimize chunking strategies and retrieval recall for AI agents

This task can be performed using Vero

Make your AI production-grade

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Vero

Vero

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We make your RAG applications and retrieval-based AI agents production-grade. Vero tests each block in your system, pinpoints exact performance bottlenecks, and fixes them. From domain-specific nuance checks to chunking-strategy robustness and retrieval recall, we stress-test every layer so you can ship with confidence.

What to expect from an ideal product

  1. Vero automatically tests different chunk sizes and overlap settings to find what works best for your specific data and use cases
  2. The platform runs comprehensive recall tests on your retrieval system to identify exactly where documents are getting missed or ranked poorly
  3. It pinpoints performance gaps in your chunking approach by testing how well your AI agent can find and use information from each chunk type
  4. Vero stress-tests your retrieval setup with real queries to show you which chunking methods give the most accurate and complete results
  5. The system provides specific fixes for chunking and retrieval problems rather than just highlighting what's broken

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