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Recipe: Unbilled work by age

Use Agentic AI Insights to see unbilled work grouped by age, with the reason it is stuck

Published: 2 November 2026

Audience

  • Finance Team

Objective

This article explains how to see all unbilled work with Claude or ChatGPT. You see delivered work that has not been invoiced yet, grouped by how old it is, with the likely reason the oldest amounts are stuck.

Prerequisites

The MCP connector is active on your organization. 
        An Admin has enabled the MCP connector for your organization.

Your AI assistant is connected.
        Your AI assistant (Claude or ChatGPT) should be connected to PSOhub.
        See How to Connect Claude to PSOhub or How to Connect ChatGPT to PSOhub.

Steps

  1. Copy the prompt exactly as written:
  2.    How much delivered work have we not invoiced yet, and how old is it?

       Show our total WIP on active projects, per customer and per project, with the date of the oldest unbilled hours on each. Group the amounts by age: under 30 days, 30 to 60, 60 to 90, over 90.

       For everything over 60 days, give the likely reason: waiting on approval, waiting on a milestone, no invoice schedule, or forgotten. Separately: billable hours that never made it onto any invoice, and the oldest of those.

       End with the three projects to chase first, and why those three.

       Show this as a dashboard: a header with the scope and date, a one-line verdict with three to five key figures, the findings ranked worst first with the reason and the amount, a table with the rest, what this answer could not see, and three actions with an owner. Use a single HTML page if you can show one, otherwise the same blocks as formatted text. Link every project, customer, person and invoice to PSOhub.

     

  3. Paste the prompt into Claude or ChatGPT and send it.

📌 Note: Contract lines need a value and an invoicing method, and hours need to be approved. Run Recipe: Is our billing data ready for deeper analysis? first.

Result

You get a dashboard with your unbilled work per customer and project, grouped by age, and the likely reason behind the oldest amounts. It ends with the three projects to chase first.

💡 Tip: Ask a follow-up question, for example:

  • Where did we invoice ahead of delivery?
  • What happens to our cash if we clear the top five this month?
  • Show the same per project manager.

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