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Custom apps & analytics

People ops dashboards, built in Claude

Ask Claude for an HR dashboard and it reads headcount, pay, review ratings, and diversity data from Taito.ai, then builds it as an interactive view you can share. One prompt, live data.

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An HR dashboard for Q3 2026 being built in Claude from live Taito.ai data: 64 people and 61.5 FTE, up 4 this quarter; a median monthly salary of €5,100; 78% of employees meeting or exceeding expectations in H1; and 46% women across 9 nationalities.

How it works

The numbers, when you need them

One prompt before the board meeting or the quarterly review. Claude pulls the records live from Taito.ai, builds the dashboard in the chat, and answers follow-up questions about it. Need a standing app instead? Build one in Lovable.

Four views, one prompt

Headcount, pay, performance, and diversity in one dashboard, built from live records. No spreadsheet export, no BI tool.

Built when you need it

Make it for the board pack or the quarterly review, then ask follow-up questions in the same chat. Nothing to maintain in between.

Your permissions still apply

Claude sees only the people data your Taito.ai role allows, so compensation stays with the people cleared to see it.

Prompt

Use Taito.ai MCP to build an HR dashboard
as an interactive artifact, with four sections:

  1. Headcount & FTE: headcount, FTE, hires
     and leavers this quarter, by department
  2. Compensation: median salary by department
     and level, total payroll cost
  3. Performance: rating distribution from
     the latest review cycle
  4. Diversity: gender and age mix, overall
     and by department

Show aggregates only, and hide any group
smaller than five people.
  • Claude
  • Taito.ai MCP

Frequently asked questions

Where does the data come from?
Straight from Taito.ai over MCP: employment records, salaries, review cycles, and employee profile fields. Nothing is exported or copied into another tool first.
Who can see compensation and diversity data?
Claude reads Taito.ai as the person asking, so the dashboard only contains what that person’s role already allows. Someone without access to salaries gets a dashboard without salaries.
How do I keep diversity data anonymous?
Ask for aggregates only. The example prompt hides any group smaller than five people, so no one can be singled out from a small team.
Can I update it next quarter?
Run the same prompt again and Claude rebuilds the dashboard from current data. Add a line to compare with the previous quarter if you want the trend.

Built to work together

Keep exploring

More workflows on the Taito.ai MCP server, or browse all MCP use cases.

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