Titus VelpulaAI consulting
A person pointing at a chart on a laptop screen.

Services / 3. Improve

Make the system ready for real work.

Check the quality, handle the exceptions, and help your team feel confident using what has been built.

How it works

  1. Measure what it does

    I build a set of test cases from real scenarios and score the system against them, so quality is a number and not a feeling.

  2. Plan for the exceptions

    Anything the system is unsure about goes to a person, with clear rules for when it should stop and ask.

  3. Hand over and refine

    Your team gets documentation and a walkthrough. We review how it is performing and fix the rough edges.

Abstract illustration of a neural network taking in and returning data.

Measured, not guessed.

For my RAG Research Assistant I built a test set of 36 reviewed questions and compared three retrieval methods. I also checked an automated reviewer against my own decisions: it agreed on 94% of them.

See the results

What you get

  • AI output evaluation and testing
  • Human review and escalation paths
  • Documentation, handover and refinement

A good fit if

  • You already use an AI tool but aren't sure how often it gets things wrong.
  • You need a person to approve some decisions before they are acted on.
  • Your team needs to own and run the system after handover.

Want to know how well your AI is working?

Talk about a review