Claude Code Usage Analytics & Activity Tracking for Engineering Teams
Capture every Claude Code session, prompt, observation, commit, and machine heartbeat across your team — and turn it into AI, Project, Developer, and Process insights. We caught 24% ghost seats on our own pilot.
One Capture Layer. Four Things You Can't See Today.
- You can't see how the AI is actually being used. Prompts, observations, skill invocations, and CLAUDE.md compliance live on each developer's laptop. You don't know which prompts work, which skills go unused, or whose CLAUDE.md is drifting from the team's. (→ AI Insights)
- You can't tell if AI is moving projects faster. Ticket throughput, DORA metrics, and per-project AI leverage aren't connected. You're spending on Claude Code without a measurable line back to delivery velocity. (→ Project Insights)
- You can't see who's stuck — until standup tomorrow. 24% of our seats were never activated. Of the rest, a 34× gap between power users (67 sessions/month) and occasional users (2/month). Real-time signal on who's blocked, who's flying, and who needs help. (→ Developer Insights)
- You can't enforce the process you wrote down. Skills mandated but skipped. Code review rules ignored. CLAUDE.md rules silently drifted. Process compliance is invisible — until something breaks in production. (→ Process Insights)
Four Signals. One 90-Second Install.
One sync agent per machine reads Claude Code's local database, your local git repos, and a process heartbeat — then ships to your org subdomain every three minutes. No VPN, no proxy, no workflow change.
Prompts
Every prompt the developer typed into Claude Code, with project path, git branch, session ID, and timestamp. Searchable in full-text — the raw signal of how engineers are actually working with AI.
Observations
Tool invocations, file reads, file edits, summaries, and skill usage — the full Claude Code session graph. Turns “what did Claude do?” from anecdote into queryable data.
Local Git Commits
Every commit on every local repo (not just Claude sessions) — author, branch, files, full diff, line stats. AI-summarized on ingest by Claude Sonnet 4.6. Ties AI usage back to shipped code.
Machine Heartbeat
Every 3 minutes: agent health, claude-mem DB status, last sync, background job state. Tells you who's actually online, who's drifted offline, and who never installed it.
Four Lenses on One Dataset.
The same capture layer feeds four dashboards. Read whichever one matches the question you're asking this week.
AI Insights
Are your engineers using AI well?
- Prompt categorization — what kinds of work the team asks Claude to do
- Skill usage — which skills are mandated, which are quietly skipped
- CLAUDE.md compliance — local files vs. golden version on
main
Project Insights
Is AI actually moving delivery forward?
- Ticket throughput per project
- DORA metrics: deploy frequency, lead time, change-fail rate, MTTR
- Per-project AI leverage — sessions and prompts attributed to each codebase
Developer Insights
Who's flying, who's stuck, who never installed it?
- Real-time daily activity per developer (no more “wait for standup”)
- Power-user vs. occasional-user vs. zero-activity classification
- Where each engineer is working, on what, with what blockers
Process Insights
Is the team following the process you wrote down?
- Process compliance — what's mandated vs. what's actually run
- Daily-skipped rules with enforcement reporting
- CLAUDE.md and skill rule violations, per developer, over time
What Activity Tracking Caught On Our Own Team
22 developers, 12 projects, four signals, one month.
Decisions Backed by Data, Not Anecdote
- Per-seat utilization report for every renewal — fact-based, not anecdotal (Developer Insights).
- DORA-aligned multipliers per project to prove AI leverage (Project Insights).
- Process compliance reporting — surface skill and CLAUDE.md drift before it hurts production (Process Insights).
- 24% unused seats — that catch alone paid for the platform in month one.
Every prompt, accounted for
- Prompt text, tool output, file paths — exportable per-user for audits.
- Data isolated per org; four-role RBAC enforced server-side.
- Self-host on your AWS for full data sovereignty.
Tracks activity across the tools your team uses
Questions engineering leaders ask
Stop Guessing. Start Measuring AI Across Your Team.
A 15-minute demo with a founder. See your team's four-insight profile in your own dashboard.