AI runs on an open budget.

We hand you the bill.

73% of companies overshoot their AI cost plan, and agentic projects overshoot it by 2.4x on average. Almost nobody knows the return, because nobody puts tokens in the denominator.

The problem in numbers

Nobody puts tokens in the denominator

Licences show up on the invoice, tokens don't. And the code AI produces carries a maintenance cost nobody is counting. The result is a budget you discover after the fact.

73%
Companies overshooting their AI cost plan
2.4x
Average overshoot on agentic projects
$200-600
Real cost per developer per month
2.5-3.5x
Healthy ROI, but only if you count tokens

Public sources: FinOps Foundation State of FinOps 2026, GitClear study on 153 million lines, 2026 productivity benchmarks.

  1. Diagnosis

    2 weeks

    Free

    The AI bill

    Real spend — licences, tokens, GPU — broken down by team and feature, share of AI-generated code and what it costs to maintain, top 5 wastes in €/year.

  2. Pilot Build

    2-3 weeks

    AI unit economics

    Every call tagged by team, feature and environment on a narrow scope: you go from «we spend a lot» to «this thing costs X».

  3. Build

    6-8 weeks

    Token governance

    Full attribution, model right-sizing, routing, caching, budgets and alerts, usage policy.

  4. Stewardship

    Retainer

    AI watch

    Continuous monitoring of cost, quality and risk. Monthly report, quarterly review.

What you get

From "we spend a lot" to "this thing costs X"

Every item is a named deliverable you can put in a contract and check on delivery.

AI spend inventory

Licences, tokens, GPU and infrastructure in a single statement, including the share that appears on no invoice.

Attribution by team and feature

Every call tagged by team, feature and environment. The argument ends and the numbers begin.

Cost per unit of value

Cost per resolved ticket, per active user, per delivered feature. Numbers a CFO reads without translation.

Model right-sizing and routing

The right model for each task, with caching and fallbacks. On targeted workloads, documented reductions of 40-80%.

Budgets, alerts and usage policy

Spend caps per person and per team, alerts before the overrun, and written rules on what can be used and how.

Generated-code quality

Separate measurement of AI-written code: how much survives, how much gets rewritten, what it costs to maintain.

Questions we get

What people ask before signing

No. We work with what you have: Claude Code, Copilot, Cursor, direct API calls. We add measurement around them, we don't replace them.

Contact us

A quote, a particular request, or simply a coffee to meet us? Write to us and we will reply to a "nano-second".

Address
Piazza Maestri del Lavoro 7
20063, Cernusco sul Naviglio (MI)
Italy
Address
Piazza dei Martiri 1
40121, Bologna (BO)
Italy