Cost allocation
Tag scheme, resource-group hierarchy, and FOCUS-normalized billing data so every dollar has a team, a product, and a reason.
Pillar 1
FinOps + AI Economics
Cloud cost discipline and AI unit economics for teams whose cloud and AI bills have started asking uncomfortable questions.
Problems we solve
What we hear on the first call
- "We can't explain why our Azure bill jumped 40% last quarter."
- "We're shipping AI features but have no idea what they cost per customer."
- "Our CFO wants a tokens-to-dollars rollup and we don't have one."
- "We tried to do FinOps internally and it stalled. We need someone who's done it before."
What we ship
Offerings
AI token economics
Azure OpenAI chargeback: tokens → dollars → business value. Per-team, per-feature, per-customer attribution.
Power BI dashboards
CFO-readable views that connect spend to the metrics your leadership actually asks about.
Signature AI Solutions arc
End-to-end: brainstorm the problem, educate the team, build the solution, set up the CoE. Optional across sprint or project shapes.
What an engagement looks like
3-week FinOps sprint (representative)
- Week 1 — Discovery: stakeholder interviews, billing export audit, tag scheme review.
- Week 2 — Instrumentation: FOCUS ingestion, Power BI model, initial unit-economics rollup.
- Week 3 — Handover: dashboard walkthrough, runbook, named owner on your side, 30-day check-in scheduled.
End state: tagged-to-the-SKU cost allocation with a Power BI rollup your CFO can read.
Proof
Our thinking, in public
Robb Dilallo's piece on the Microsoft FinOps Blog — Managing Azure OpenAI costs with the FinOps toolkit and FOCUS: turning tokens into unit economics — is a good sample of how we think about AI cost work.
Read the article on Microsoft Tech Community →