Built for teams navigating AI at scale
We work with the people responsible for making AI investments decidable, defensible, and value-driven.
CFO & Finance
Budget owners, Controllers
I need predictable AI budgets I can defend to the board.
WHAT YOU GET
Driver-based forecasting, not "last month + 10%"
Clear spend-to-outcome linkage for ROI discussions
Audit-ready allocation across teams and project
CTO & Engineering
Tech leads, Platform teams
I need governance that doesn't slow down our teams.
WHAT YOU GET
Controls that scale with your architecture
Tagging strategy that engineering can actually use
Shared language with Finance — no more translation
Compliance & Risk
Auditors, GRC teams
I need audit-ready cost allocation — traceable and defensible.
WHAT YOU GET
Full traceability: who used what, when, and why
EU compliance built in — GDPR, AI Act, NIS2
Audit-ready allocation across teams and project
TROIAI For FinOps across your maturity stage
Validate (PoC). Control (Production). Optimize (Scale).
Crawl
Is this worth building?
crawl
Quick and pragmatic — but not blind.
-
Define scope, stakeholders, success criteria, and decision gates
-
Create a minimum viable cost model (drivers, assumptions, risk flags)
-
Structure PoC → Production handover so nothing “dies” after the demo
-
Optional: delivery support with your teams or ours
-
-
PoC-to-Production Log
-
Risk & Assumption Sheet
-
Decision Brief (1 page)
-
Start the PoC Readiness Check
Walk
Can you defend the spend?
Walk
From experiment to production — Finance, Engineering, and Compliance aligned.
-
Planning & estimating (scenarios: best / expected / worst)
-
Budgeting (allocation and shared cost strategy)
-
Forecasting (driver-based, not “last month + x%”)
-
Spend → Outcome KPI chain (value tracking you can defend)
-
-
Driver-based forecast model
-
AI Allocation Blueprint
-
ROI / Value Scorecard
-
Book the Cost Model Workshop
Run
Scale without losing control
Run
Reduce cost and risk — without losing compliance or security.
-
Allocation & tagging strategy for AI (who uses what, why, and how much)
-
Data ingestion across public cloud, private cloud, data centers, and SaaS
-
Reporting for Finance, Engineering, Product, and Compliance
-
-
Architecture optimization (inference patterns, batching, caching, retrieval)
-
Rate optimization (commitments, capacity strategy, spot where safe)
-
Licensing & SaaS governance
-
Workload optimization (retraining frequency, pipeline efficiency, token discipline)
-
-
AI Spend Dashboard specification
-
Anomaly Playbook
-
Optimization Backlog (prioritized)
-
Request an Optimization Audit
AI is scaling fast
— achieve audit-ready cost control with TROIAI.
Our team helps you bring AI under financial control — with reliable forecasting, clear accountability, and ROI-linked decisioning at scale.
Discover how our FinOps for AI framework adapts to your AI workloads, cost drivers, and compliance requirements
allocation model, forecasting approach, and risk controls for your organization
Learn how we bring your AI into auditable, production-ready operation — fast

