Generative AI ROI Platform Pay-i Raises $4.9M Seed Round Led by Fuse Partners and Tola Capital to Track and Forecast GenAI Returns

Led by Fuse Partners and Tola Capital, the seed round backs a new class of ROI-intelligence platform designed to track and forecast GenAI returns in real time

Enterprises are investing heavily in GenAI but struggle to measure its ROI, a critical factor C-suite executives are now demanding. Pay-i, a new value-intelligence platform for GenAI, is emerging from stealth today to solve this. The company announced $4.9 million in seed funding co-led by Fuse Partners and Tola Capital.

Pay-i's platform provides product, finance, and engineering leaders with a real-time dashboard linking every model call, prompt, and token to measurable business outcomes for specific use cases. This allows users to 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 projects those returns forward, enabling companies to prioritize what works, sunset what doesn't, and scale GenAI with confidence before it even goes into production.

Most teams today measure success in token counts or latency, metrics that don't capture business value or justify costs. Pay-i solves this by closing the loop from GenAI actions to KPIs. For instance, customer support teams can assign a $5,000 value to fully automating tier-2 support cases with an agent. Pay-i then tracks how each change in the agent's capabilities impacts case completion time, with faster times driving greater value. Teams can A/B test multiple versions of the agent or prompt to see which delivers the strongest return on throughput, CSAT, or other KPIs.

"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. They then A/B test different agents or prompts for an email campaign and see how each change impacts task completion time, revenue conversion, or KPIs like CSAT. Pay-i also 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 has since briefed F500 boards, universities, members of Congress, and UN delegations on AI economics. He co-founded Pay-i with 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 has 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. This is 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 reshape 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