• ISOLATED
  • CONFIRMED
  • DATA-DRIVEN
  • HUMAN

How to validate process optimization results with your AI

Connect the Galileo Experimental Prover to your AI client to stop guessing which changes actually moved the needle.

Ask AI about this page

Short answer

How can I tell if a workflow change actually worked?

Your AI uses the Galileo Experimental Prover to isolate single variables, ensuring that observed improvements come from your specific change rather than external noise. This process strips away confounding factors to give you a clean look at the causal link. You get a breakdown of the isolated impact below.

The results you get.

Clearer experiment outcomes.

The AI handles the statistical heavy lifting to give you these four outcomes.

ISOLATED

Single variable focus

The AI identifies and holds constant all other factors. You get a clear view of the specific change you made.

CONFIRMED

Causal validation

The agent confirms if the change actually caused the result. This prevents you from chasing false positives.

DATA-DRIVEN

Cleaned datasets

The AI processes your logs to remove noise. You receive a refined set of data points for analysis.

HUMAN

Final decision making

The AI presents the isolated findings to you. You decide whether to roll out the change or iterate further.

The workflow

What your AI does when the experiment starts.

The AI takes over the math so you don't have to manually hunt for noise in your logs.

  1. Identify variables

    Your agent scans your existing process logs to find every moving part in the workflow.

    validate_galileo_experiment

  2. Isolate the change

    The AI separates the specific variable you modified from the rest of the environment.

    validate_galileo_experiment

  3. Run the validation

    The agent executes the mathematical check to see if the delta is statistically significant.

    validate_galileo_experiment

  4. Report findings

    The AI summarizes whether the change was the actual driver of the improvement.

    validate_galileo_experiment

Try it

Copy these to start.

Use these prompts to kick off an experiment with your agent.

Starting points

Replace the bracketed text with your specific workflow details or data sources.

Galileo Experimental Prover Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_isqYV5nylEKAxwmBsGWpbc0CJmDH7Xhz0HL04bd3/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Galileo Experimental Prover capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "galileo-experimental-prover-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_isqYV5nylEKAxwmBsGWpbc0CJmDH7Xhz0HL04bd3/mcp"
    }
  }
}
Copy into chat04

  • Validate the results of my recent change to the checkout workflow in the production logs.

  • Isolate the impact of the new API latency settings on our total processing time.

  • Run an experiment to see if the updated routing logic actually improved throughput in the main database.

  • Check if the change to the user onboarding sequence caused the increase in conversion rates.

  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Start here

Connect Galileo Experimental Prover once, then ask.

Just link the MCP to your preferred client. Your credentials stay encrypted, and you can start running experiments immediately.

Connect Galileo Experimental Prover to your AI

FAQ

How the validation behaves

  • 01

    Can the AI change my production settings?

    No. The AI only reads data and performs validation. It cannot modify your live workflows or settings.

  • 02

    Does the AI delete my experiment logs?

    No. The AI only accesses the logs to perform the validation; it has no permission to delete any data.

  • 03

    How does it handle multiple changes at once?

    It is designed to isolate single variables. If you change five things at once, the AI will tell you it cannot confirm which specific change caused the result.

  • 04

    What kind of data does it need?

    It needs access to the logs or datasets where the workflow changes and the resulting metrics are recorded.

  • 05

    Can I use this with any AI client?

    Yes, as long as your client is MCP-compatible, like Claude, Cursor, or Windsurf.

  • More questions about Galileo Experimental Prover? The Connector page answers them. See everything the Galileo Experimental Prover Connector can do

Connect Galileo Experimental Prover to Claude, Cursor, ChatGPT & more