• COHORT AGE
  • VELOCITY
  • LIQUIDITY
  • HUMAN

How to analyze accelerator exit maturity with your AI

Connect your cohort data to your AI client to see if your exit numbers are actually improving over time.

Ask AI about this page

Short answer

How do I check if my accelerator's exit success is actually scaling?

Your AI calculates exit performance by normalizing liquidity events against the age of each company cohort. This reveals whether your track record is improving or if you're just seeing late-stage exits from older companies. You'll get a clear view of true performance velocity.

The outcomes of this analysis

Where your insights land.

Once the data is processed, your AI delivers these specific outcomes.

COHORT AGE

Normalized exit metrics

The AI uses calculate_exit_performance to adjust exit values based on how long companies have been in the program. You get a fair comparison between new and old cohorts.

VELOCITY

Performance trends

You'll see if the time to exit is shrinking or growing across different years. This identifies if your selection or support is getting better.

LIQUIDITY

Realized success rates

The AI maps actual exits against the total number of companies in each cohort. This shows the true percentage of successful exits per vintage.

HUMAN

Strategic decisions

The AI provides the math, but you decide how to adjust your investment thesis or program structure based on these trends.

The workflow

What your AI does when the data arrives.

The AI handles the heavy math so you can focus on the implications.

  1. Ingest cohort data

    Your AI reads your historical company lists and exit records to build a baseline.

    calculate_exit_performance

  2. Normalize for age

    The agent adjusts exit values so a 5-year-old company isn't unfairly compared to a 1-year-old company.

    calculate_exit_performance

  3. Identify trends

    The AI looks for patterns in exit timing and value across different program years.

    calculate_exit_performance

  4. Summarize findings

    Your AI presents the adjusted performance metrics in a format you can use for reporting.

    calculate_exit_performance

Try it

Copy these to start.

Use these prompts to kick off the analysis in your chat window.

Starting points

Replace the bracketed text with your specific file names or sheet names.

Accelerator Track Record Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_ycqMOekfQi9B5f3SZDHLpw46siRrpNpBThWadHSB/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 — Accelerator Track Record capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "accelerator-track-record-metrics-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_ycqMOekfQi9B5f3SZDHLpw46siRrpNpBThWadHSB/mcp"
    }
  }
}
Copy into chat04

  • Analyze the exit performance in [Sheet Name] and adjust for cohort age.

  • Compare the exit velocity of the [Year] cohort against the [Year] cohort.

  • Calculate the normalized exit value for all companies in [CSV File].

  • Show me the trend of exit success rates by cohort age using [Data Source].

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

Start here

Connect Accelerator Track Record Metrics once, then ask.

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

Connect Accelerator Track Record Metrics to your AI

FAQ

How this task behaves

  • 01

    Can the AI change my original spreadsheet data?

    No. The AI only reads your data to perform calculations; it cannot modify or delete your original files.

  • 02

    Does the AI handle the data cleaning for me?

    The AI can process the data provided, but it cannot fix broken or missing data in your source files.

  • 03

    How does it handle companies that haven't exited yet?

    The tool uses the cohort age to differentiate between companies that are still in their growth phase and those that have reached liquidity.

  • 04

    Can I use this with any AI client?

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

  • 05

    What happens if my data is in a different format?

    The AI will attempt to interpret the structure, but for the best results, ensure your cohort ages and exit values are clearly labeled.

  • More questions about Accelerator Track Record Metrics? The Connector page answers them. See everything the Accelerator Track Record Metrics Connector can do

Connect Accelerator Track Record to Claude, Cursor, ChatGPT & more