Pay-i raises $4.9m to measure real-time GenAI returns

Pay-i has emerged from stealth with seed funding of USD $4.9 million to address enterprises' challenge of measuring returns on generative AI (GenAI) investments.

The funding round was co-led by Fuse Partners and Tola Capital and included support from Firestreak, Pear VC, Gaia Capital, and angel investors from Fortune 100 companies. The company is introducing a value-intelligence platform that enables organisations to track and forecast GenAI returns in real time, even before projects move into production.

Pay-i's founders include Chief Executive Officer David Tepper, Chief Technology Officer Doron Holan and Chief Operating Officer Erik Winters. Tepper spent 19 years at Microsoft, contributing to Azure's GenAI consumption strategy and holding patents in GenAI since 2011. Holan served 27 years at Microsoft as a core architect for Windows and Azure's throttling layer. Winters brings experience in scaling early-stage companies in the finance and SaaS sectors.

Most organisations are currently unable to provide clear evidence that their GenAI investments are delivering business value, as many measure AI initiatives using technical metrics such as token counts or system latency. Pay-i addresses this by providing product, finance and engineering leaders with dashboards that connect model activity to specific business outcomes, such as revenue growth, task completion time, and customer satisfaction (CSAT) uplift. The platform allows users to set explicit monetary or time values for key performance indicators (KPIs), compare multiple versions of use cases, and observe in real time which model, agent, or prompt yields the greatest return.

"The C-suite doesn't need another usage chart – they need proof and a forecast. 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," David Tepper, co-founder and CEO of Pay-i, said.

Enterprise teams are already using Pay-i to assign concrete dollar values to features enhanced by GenAI, including customer support copilots and AI-generated reporting tools. They can conduct A/B tests among agents or prompts in production, tracking the impact of changes on task completion times, revenue conversion rates, or CSAT figures. Pay-i's forecasting tools enable companies to gauge likely business impacts even before a full rollout.

Tepper and his co-founders' experience with large-scale cloud implementations informed the platform's focus on bridging the gap between operating costs and realised business value. This is particularly pertinent to GenAI, where unit economics can be obscured by factors such as token-based billing, multimodal inputs, and agentic workflows.

"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 improved ROI clarity is increasing as enterprise GenAI investment is projected by IDC to reach USD $632 billion by 2028. According to the company, 72% of Chief Information Officers have identified ROI measurement and forecasting as their top barrier to wider adoption of GenAI technology.

"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," Lari Hämäläinen, Senior Partner at McKinsey, addressed the transition occurring as GenAI moves from experimental projects to production-critical functions.

"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," John Connors, former CFO of Microsoft and Operating Partner at Fuse Partners, commented on the pressures facing business leaders.

"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," Sheila Gulati, Managing Director at Tola Capital, said.

Pay-i's funding will support further product development and expanded access for enterprise teams seeking to optimise their GenAI deployments. The platform is available across all major cloud providers and models and is live with early enterprise customers. Pay-i also works with AWS ProServe to provide consulting and integration capabilities for tracking GenAI value metrics, supporting deployment on AWS and instrumenting Bedrock workloads.

"The companies that treat GenAI as an economic strategy, not just a technical one, will win this decade," stated Tepper. "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."