How to identify and fix performance bottlenecks in retrieval-based AI systems

How to identify and fix performance bottlenecks in retrieval-based AI systems

This task can be performed using Vero

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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 each component of your RAG system to spot exactly where slowdowns happen, saving you from manually checking every part
  2. It runs targeted stress tests on your chunking strategy to find out if your text splitting method is creating retrieval delays
  3. The platform checks domain-specific details that might be causing your system to miss relevant information and slow down response times
  4. Vero measures retrieval recall performance to identify when your system isn't finding the right documents fast enough
  5. It provides specific fixes for the bottlenecks it discovers, rather than just pointing out problems without solutions

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