Enterprise spending on GenAI is surging, but clear proof of ROI remains elusive. Most companies can’t answer the simplest question boards are now asking: is this actually working?
Pay-i, a new value-intelligence platform for GenAI, is coming out of stealth today with $4.9 million in seed funding to solve that.
The round was co-led by Fuse Partners and Tola Capital, with participation from Firestreak, Pear VC, Gaia Capital, and angel investors from Fortune 100 companies.
Today, most teams still measure success of their AI initiatives in token counts or latency – metrics that don’t capture business value or justify costs.
Pay-i gives product, finance, and engineering leaders a real-time dashboard that links every model call, prompt, and token to measurable business outcomes for specific use cases, like revenue growth, task completion time, or CSAT uplift.
Users can assign explicit dollar or time values to KPIs, compare multiple versions of a use case, and instantly see which model, agent, or prompt delivers the strongest return.
A built-in forecasting engine then projects those returns forward – so companies can prioritize what works, sunset what doesn’t, and scale GenAI with confidence before it even goes into production.
“The C-suite doesn’t need another usage chart – they need proof and a forecast,” said David Tepper, co-founder and CEO of Pay-i.
“Pay-i pinpoints which GenAI use cases create net-new value today, quantifies that value in dollars or hours, and predicts how it will compound tomorrow. Leaders can double-down on winners and reach ROI faster.”
The product is already being used by enterprise teams to assign hard dollar values to GenAI-enhanced features – like customer support copilots or AI-generated reports – then A/B test different agents or prompts in production.
Pay-i tracks how each change impacts task completion time, revenue conversion, or KPIs like CSAT – and forecasts the business impact before full rollout.
Tepper previously spent 19 years at Microsoft and was a leader in Azure’s internal GenAI consumption strategy. His first patent on GenAI dates back to 2011. He’s since briefed F500 boards, universities, members of Congress, and UN delegations on AI economics.
He co-founded Pay-i alongside CTO Doron Holan, who spent 27 years at Microsoft and was a core architect for Windows and Azure’s throttling layer, and COO Erik Winters, a veteran operator who scaled early-stage companies across finance and SaaS.
The product reflects what they learned working with the largest cloud buyers in the world: traditional cost tooling stops at usage, while real decision-making happens where cost meets value.
That’s especially true in GenAI, where token-based billing, multimodal inputs, reasoning models, and agentic workflows have made unit economics opaque and ROI harder to track than ever.
“With traditional software, we could track exactly how features were used,” added Holan. “But with GenAI, that visibility gets lost. Pay-i closes that gap and shows exactly where value is being created, in real time.”
The need for clarity is only growing. IDC projects enterprise GenAI investment will top $632 billion by 2028, but 72% of CIOs cite ROI measurement and forecasting as their #1 blocker.
“Generative AI is graduating from pilots to mission-critical production. Enterprises are rolling out knowledge augmentation tools, automated workflows, and starting to create agentic services that re-shape core operations and customer journeys.
“Scaling and managing this responsibly requires two disciplines: high-fidelity observability of entire GenAI use cases and rigorous focus on the impact of these systems through understanding the unit economics and business KPIs affected.” said Lari Hämäläinen, senior partner at McKinsey.
“Across the C-suite, patience for open-ended GenAI spending is wearing thin. Pay-i finally gives leaders the data-backed clarity to invest with conviction, transforming GenAI from an opaque cost center into a growth engine,” said John Connors, former CFO of Microsoft and operating partner at Fuse Partners.
“Pay-i turns every AI decision into a clear cost-to-value ratio, letting enterprises see, in real time, how model and design choices affect their metrics. This transparency enables businesses to control their AI spend and allocate resources optimally. Pay-i provides a roadmap for the all-important transition to AI,” said Sheila Gulati, managing director at Tola Capital.
With the new funding, Pay-i will accelerate product development, and bring its platform to more enterprise teams looking to scale GenAI with precision.
Already live with early customers, Pay-i is now generally available across all major cloud providers and models – offering decision-makers a long-overdue solution to the GenAI value gap.
Pay-i and AWS ProServe are providing a customer solution that combines AWS ProServe’s expertise consulting customers on value tracking with Pay-i’s software to instrument GenAI value metrics. Pay-i is deployed to customers on AWS and can instrument Bedrock workloads.
As Tepper puts it: “the companies that treat GenAI as an economic strategy, not just a technical one, will win this decade.” Pay-i is building the operating system for that shift – one where every GenAI investment comes with a business case, a benchmark, and a blueprint to scale.
