Measure AI adoption.
And its impact on delivery.
See who uses AI coding tools, how much your teams rely on them, and how your delivery changes as adoption grows. Across GitHub Copilot, Cursor, Claude Code and LiteLLM.
14-day free trial on every plan, no credit card required.
Licenses are easy to count.Value is not.
Axify brings the usage of every AI assistant into one view, shows who gets value from it and ties it to how your teams deliver.
Usage across every tool
Active users, interactions, tokens and last usage, for each AI assistant and each person.
Daniel Roy
Maxime Côté
Olivier Gagnon
3.2K0.9B3 days agoWho is moving up, and who is slipping
The biggest score gains and drops over 30 days, so you know where to follow up.
Daniel Roy88↗ +33
Maxime Côté57↗ +19
Olivier Gagnon58↘ -36By contributor, team, project and group
Each person’s score and level on all three pillars, with the variation over 30 days.
Daniel Roy97+2EliteEliteVery steady
Maxime Côté93=EliteHighVery steady
Olivier Gagnon58-36ModerateHighIrregularLevels over time
The share of your contributors at each level, week after week, so you see whether the mix improves.
One score out of 100.Three pillars behind it.
Each contributor is ranked against a reference cohort. A team or organization score is the average of its contributors’ latest scores.
Reflexive use
How much AI is a reflex: the number of active days over the last 28 days.
Reliance
How much people lean on AI when they use it: gross cost per active day.
Trust
How steady the habit is: the regularity of the gaps between usage days.
AI is a lever.Delivery is the goal.
Axify puts AI adoption next to cycle time, throughput and DORA metrics. In Explore, compare AI usage, tokens or cost with PR and issue throughput, by team or contributor.
Track what AI costs, and where it’s heading
Gross cost by tool, model, team and contributor, with a projected trend.
Explore AI cost →Ask in plain language
In the app, ask about a project or a team, right where you already look at your data.
Discover Axify Intelligence →Ask about AI adoption.From the AI tool you already use.
Connect the Axify MCP server to Claude, ChatGPT or Cursor and ask about scores, usage and delivery in plain language. Answers come from your Axify data.
- Understand why a team’s score dropped
- Compare AI usage and PR throughput from team to team
- Prepare a summary for your next leadership update
Two teams dropped this month:
Search Platform went from 85 to 77. Reflexive use fell from High to Moderate, with fewer active days over the last 28 days.
Mobile App went from 79 to 76, mostly on Trust: usage became less regular.
Reliance is stable for both teams.
From adoption to impact.In three steps.
Connect your AI tools
GitHub Copilot, Cursor, Claude Code and LiteLLM, read-only. LiteLLM also covers models routed through your proxy.

Connect your delivery tools
GitHub, GitLab, Bitbucket, Azure DevOps and Jira bring in pull requests, issues and deployments.



Act on the gaps
See who gets value from AI and who needs support, then follow the effect on delivery.
Frequently asked questions
Start measuring AI adoption.
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