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Solutions

You can't improve AI that you don't measure.

Clairet ensures each AI use case starts with a baseline and the metrics it will be judged by. Make decisions based on data, not anecdotes.

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What you'll work in
  • Initiatives
  • Roadmap
  • Outcomes

Sound familiar?

Everyone says it is working. Nobody can show it.

  • You approved the budget. You cannot say what it returned.
  • Every pilot is declared a success. None of them had a baseline.
  • Developers feel faster. The defect rate says otherwise.
  • You saved time. But blew the budget on tokens.

The evidence so far

Adoption is up. Returns are not.

  • Felt faster, was slower

    −19%

    slower: A controlled study found for developers using AI assistance, while they believed they were 20% faster.

    METR, 2025

  • No productivity gain

    89%

    of firms report zero impact on labor productivity from AI over the past three years.

    NBER

  • Confidence without evidence

    8%

    of organizations can measure AI ROI, while 76% of executives are confident AI is delivering 'meaningful business value'.

    KPMG, 2026

What changes

From declared to demonstrated.

  1. Success is declared at the end, by the team that ran it.

    Baseline

    Where you were before the initiative began, captured before a dollar moves, and the metrics it will be judged by.

  2. Funding goes to the loudest team.

    Same terms

    Proposals enforce disciplined AI usage and everyone is held to the same policy.

  3. Nobody can list what is running, let alone what it costs.

    One roadmap

    Align each initiative with their owner, timeline and target outcome, all in one place.

How it works

Measure before, during and after.

  1. Baseline

    Capture where you are before the work starts. Without it there is no return to prove.

  2. Commit

    Every proposal names its owner and the metrics it will be judged by, before funding.

  3. Measure

    Track the metrics the owner committed to, alongside readiness, as the work runs.

  4. Decide

    Scale what works. Fix what does not. Stop what never will. On evidence, not sentiment.

What changes

Tracking AI outcomes with Clairet

  1. 01

    Accountability replaces absence.

    Adopt new AI use cases quickly and transparently with a standardized process. Don't let good ideas become shadow AI.

  2. 02

    Hard values replace vague feelings.

    Track metrics the owner committed to, alongside risk and readiness. Scale what works based on evidence, not sentiment.

  3. 03

    Your AI is visible, owned, and measured.

    Align each AI initiative and use case on a roadmap from beginning to end. No orphaned projects. No invisible spend.

How Clairet fits

Better together

  • Usage & adoption analyticsShow you how often AI gets used.

    Impact

    Clairet connects model usage to use cases and outcomes, so you can see which investments are actually moving the work forward.

  • AI spend managementShow you what AI costs.

    Return

    Clairet fills in the other half of the equation: what your money is getting you.

  • Productivity analyticsShow you how fast work moves.

    Proficiency

    Clairet shows who's using AI well, coaches everyone to get better, and shows where everyone actually works.

  • BI & financial reportingShow you business results.

    Attribution

    Clairet links those results back to specific AI initiatives and use cases, so you know what to fund next.

Nothing is replaced. Every tool you already have does its job better.

Built for your whole organization

What changes, by role

  • Executives

    Evidence

    Every initiative carries a baseline and metrics from day one.

  • IT & Technology

    See

    Discover sanctioned and unsanctioned AI across the organization.

  • Risk & Compliance

    Evidence

    Decisions, reasoning, and policy basis are recorded automatically.

  • HR & Learning

    Voice

    Trained, trusted employees help choose what's adopted next.

Common questions

Questions, answered.

Is this MLOps monitoring?
No. MLOps tells you whether a model works. Outcome Tracking tells you whether the initiative worked for the business, which is the question the board is asking.
What if an initiative has no obvious metric?
Then it is not ready to fund. Naming a baseline and a metric is the first step in Clairet, and it is the step most failed AI projects skipped.

Ready to bring order to your AI strategy?

Talk to the Clairet team. We will show you what structure looks like in practice.

Request a Demo