Aidealy

Aidealy is an AI engineering analytics tool that measures the productivity of developers and AI agents from what actually reaches production. It reads activity from Git and AI code editors, connects it into a queryable graph and lets you ask questions in plain English, with no dashboards or queries. It is aimed at engineering leaders, CTOs and R&D directors at teams of 10 to over 1,000 people.

What is Aidealy used for?

It tells you what each person and each agent contributes to the code you ship, and how much rework they cause. Aidealy computes the Aidealy Productivity Rank, a signed score per contributor over 7-, 30- and 90-day windows that rewards real contribution and subtracts for bugs and later corrections. The site itself stresses that the number is a starting point for investigation, not a verdict.

How does Aidealy work?

Aidealy uses history from GitHub, GitLab, Bitbucket and Azure DevOps and sessions from Cursor and Claude Code through its own extension. It treats a commit merged into the default branch as having reached production and labels each line as AI-written or human-written from content fingerprints rather than a detector. It also computes real hands-on hours per pull request and loads past history in an initial backfill.

Who is Aidealy for?

• Engineering directors who must explain to the board what AI contributes.
• Teams that want to see AI spend by model and by engineer.
• Quality leads looking for which repositories improve or decline.
• Organizations already working with agents that open and merge code.

Aidealy pros and cons

Its strength is mixing humans and AI agents in one measurement with plain-English questions. On the downside, the extension is for Cursor and hours tracking is a measured floor, not a census; issue tracker integration is listed as coming and the tool does not replace your task tracker.