FinOptik operates at the intersection of AI, cloud economics, and enterprise finance
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When organizations contact us:
"We've had a Lead Director of AI FinOps role open for eight months. Our recruiter now tells us the skillset doesn't exist in one person."
"Our CFO said he needs numbers, not stories. We don't have numbers he'll accept."
"The board is asking what our AI program is actually returning and we don't have a defensible answer."
"We're about to commit $40 million and nobody outside of IT has validated the business case."
"Finance doesn't trust our cloud and AI numbers. That mistrust is now slowing down approvals."
"Our AI spend is growing faster than anyone can explain and there's no accountability model."
"It takes our teams months to justify a new workload. We're losing time we can't get back."
"We can't tell what any individual AI initiative actually costs end to end."
If any of these sound familiar, contact sales@finoptik.io.
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What we do.
Cloud and AI Business Case. Pre-investment. The POC is done and Finance needs a defensible case before the board approves production spend. Fixed scope, 4 to 6 weeks.
FinOps Strategy for Cloud and AI. Post-commitment. The operating model, governance, tagging, unit economics, and Center of Excellence. Fixed scope, roughly 26 weeks for a working foundation.
Consumption Management for AI and Cloud. Ongoing. Model selection trade-offs, unit economics tracking, commitment optimization, board reporting. Monthly retainer, cancel anytime.
Why tooling isn't enough.
Tooling platforms like Cloudability, Apptio, and Vantage are great to provide visibility and reporting.
The harder problem is that Finance and Engineering are two different cultures with two different languages. Engineering talks in instances, tokens, and utilization. Finance talks in accruals, variance, materiality, and forecast confidence. Both are describing the same spend, and neither fully trusts the other's version of it. No dashboard closes that gap, because the gap is not informational. It is cultural.
That is the work we do. We sit between the two organizations and translate, and more importantly, we teach each side to speak the other's language well enough that they stop needing a translator. Engineering leaders learn to frame consumption decisions in terms a CFO recognizes as rigorous. Finance teams learn enough about cloud and AI cost behavior to ask better questions and extend trust where it is warranted.
When that works, the change is structural. Business cases stop getting sent back for a second opinion. Budget conversations get shorter. Workload approvals that took months take weeks, because Finance has enough confidence in the numbers to move.
FinOptik is tool-agnostic. We will work with whatever platform you have, or help you select one, but the platform is not the deliverable. The deliverable is an organization where Finance and Engineering can have a productive conversation about technology spend without a third party in the room.
