Yarken launches AI Economics platform to give CFOs cost visibility

Yarken, a London and New York-based FinOps and Technology Business Management (TBM) platform, has released what it describes as a CFO-focused AI Economics module, designed to link enterprise AI consumption costs directly to the General Ledger. The launch comes as organisations grapple with a growing disconnect between accelerating AI spend and the financial controls that govern every other cost line in the business.

The platform's central proposition is that existing FinOps and Tokenomics tools capture only the most visible AI costs, typically token charges, while missing the fully loaded picture: model licensing, GPU-instance hours, AI specialist labour, consulting, and non-AI infrastructure costs that support AI workloads. Yarken says its module normalises all of these into a single cost model and maps them to business units, projects, teams and individual AI agents, enabling what the company calls Return on AI, or RoAi, analysis.

Ravi Kuppan, founder and chief executive, said: "To date, the AI race has largely played out away from the tried and proven processes and systems which CFOs use daily to operate their businesses. Massive AI adoption breaks the decade-long connection between books of accounts, IT systems of records and finance professionals and is now unsustainable as AI spend moves so fast."

What the platform does

Yarken's AI Economics module is described as agentic AI-native, meaning it deploys its own automated agents to run continuous anomaly detection and cost-allocation recommendations rather than relying on month-end batch reporting. Key capabilities include daily cost allocation across models, vendors and business units; integrated AI capitalisation tooling to separate capitalised development spend from operational expenditure; and forecasting that adjusts dynamically when token pricing changes.

The capitalisation feature is notable for finance teams under pressure from auditors: accounting standards for internal AI development costs remain an active area of interpretation globally, and a defensible, auditable split between capital and operational AI expenditure addresses a genuine compliance pain point for listed companies and those operating under IFRS or US GAAP.

The company also disclosed that it became a founding member of the Linux Foundation's Tokenomics Foundation earlier this year, joining a group that reportedly includes JP MorganChase, Oracle, SAP and ServiceNow. Membership of the foundation adds standards credibility to Yarken's positioning, though the foundation itself is newly established and its governance output is yet to be published.

Market context

The AI cost management space is expanding rapidly. Hyperscalers offer their own spend dashboards, and a number of specialist FinOps vendors, including Apptio (now part of IBM), Flexera and newer entrants focused on LLM-specific cost attribution, compete for the same enterprise buyer. The differentiated claim Yarken is making is General Ledger integration rather than operational dashboarding alone, which targets the CFO rather than the FinOps practitioner or cloud architect as the primary buyer.

Enterprise AI budgets are under increasing board scrutiny as the initial wave of AI project investment runs up against demands for demonstrable return. That pressure makes CFO-grade visibility a commercially rational sell. Yarken has not disclosed customer names, commercial pricing, or the number of enterprises currently on the platform, all of which will be the key signals for analysts assessing whether the product has moved beyond early adopters. An interview with CEO Ravi Kuppan is available via the company's PR contact.