AI usage tracking and reporting

AI usage reporting that stays out of the way.

Understand your team’s AI spend and the work behind it. Simple setup, clear reports, and built to collect metadata only: never prompts or source code.

Pre-launch. Demo figures are synthetic.Capability status

SymentrioAcme Engineering Demo data
Platform team · Aug 2026 · USD31 Aug · UTC

Where the spend went

Consumption basis

$52,000 estimated, grouped by the status of the work.

  • Production observed42%
  • Merged, awaiting production18%
  • Open work16%
  • Approved non-code work10%
  • Closed without merge4%
  • Unresolved10%

Built for the tools your team already uses

Initial integration focus

Claude CodeCodexCursorOpenCodeGrok Build+61 more

How it works

Track, link, report.

  1. 01

    Track usage and cost

    By developer, tool and repository, with the cost basis kept explicit.

  2. 02

    Link spend to work

    Sessions follow their commits into main. Every link shows how it was made.

  3. 03

    Report what happened

    Merged, in progress, non-code and unresolved work stay separate.

The evidence

Spend, usage and delivery on one timeline.

Follow a single session from its cost to the commit, the merge and the deployment.

Spend, usage and deliveryDemo data

Platform team · Aug 2026 · UTC · $52,000 estimated consumption

Chart summary. Spending: daily estimated spend totals $52,000 for the month, peaking at $2,930 on 19 Aug and low at weekends. Usage: 97 agent sessions, almost all on weekdays. Delivery: commits on 11 days, 6 merges into main and 4 production deployments. The highlighted trail follows.

  1. 20 AugSession · $240 estimated
  2. 20 AugCommit on the approved branch
  3. 26 AugPR #142 merged into main
  4. 28 AugProduction deployment
The highlighted session is followed to its commit, merge and deployment. Grey marks are the team’s other activity.

Honest accounting

A signal, not a score.

Unmerged work isn’t waste and a merge isn’t ROI. Every category stays visible, so the team can discuss what the spend supported.

  1. Production observed42%
  2. Merged, awaiting production18%
  3. Open work16%
  4. Approved non-code work10%
  5. Closed without merge4%
  6. Unresolved10%
Platform team · Aug 2026 · $52,000 estimated consumption · Demo data

Who it’s for

For the person who has to explain the bill.

Engineering leads

Report on AI spend with the work behind it, and make the case for the next budget.

Developers

See your own usage, add context to your work, and never get ranked by token count.

Trust

Metadata only.

Usage counters, identifiers and delivery states cross the line. Prompts, responses and source code are excluded by design.

Crosses the line

  • Usage counters and timestamps
  • Repository, commit and PR identifiers
  • Delivery states and coverage

Stays out

  • Prompts and responses
  • Source text and diffs
  • Tool arguments and outputs

Good questions

Before you ask.

Does a merged pull request prove ROI?

No. A merge is a delivery milestone, not a business outcome. Symentrio keeps merged, deployed and in-progress work separate so the team can discuss value with the evidence in view.

Will this rank our developers?

No. Authorized leads can inspect usage and work associations, but there are no productivity scores. Research, incident response and unfinished work keep their context.

What do we need to get started?

One engineering group, the coding tools you already use and a GitHub connection. Sources and scope are confirmed during setup.

Symentrio

See the work behind
your AI spend.

Start with one team and the coding tools your developers already use.

Talk to us

A scoped pilot: usage, costs and delivery evidence.