Ascerta raised $18M to tie AI spend to results

Ascerta raised $18 million in a Series A to tell enterprises which AI bets are worth scaling.

Dell Technologies Capital led the round with Hitachi Ventures, BGV and Wipro Ventures, lifting total funding to $22.9 million.

The Bellevue company formerly known as Pay-i had raised a $4.9 million seed in May 2025 focused on AI cost management.

Founders David Tepper, Doron Holan and Erik Winters spent 19, 27 and Microsoft veteran years building GenAI strategy and hyperscale throttling for hundreds of billions of daily requests.

They rebranded to Ascerta to expand from cost visibility to what they call Enterprise AI Management.

That pitch targets CIOs, CFOs and AI leaders who can count tokens, licenses and agent runs but cannot tie them to business outcomes.

Ascerta deploys alongside existing systems and connects to Microsoft Copilot, Amazon Bedrock AgentCore, Salesforce Agentforce and coding agents including GitHub Copilot, Claude Code and Codex.

It traces use by person, team and tool and maps each use case to business KPIs, while measuring true cost down to sub-token charges, hidden fees and discounts.

Three products package the work: Atlas for portfolio ROI, Forge for coding agent productivity, and Convoy for firms provisioning their own capacity.

Customers including Atos, Wipro and global insurance carriers use it to price AI features, recover failed agent runs and surface Shadow AI.

Ascerta says those customers have seen 47% improvement in AI ROI, 24% faster agent launches and 86% less wasted AI spend.

Those figures are company reported without independent audit, so buyers will need to validate them on their own data.

AWS notes Enterprise AI brings transparency and control for sensitive data access and explainable AI, a threshold any system of record must clear.

Raman Khanna, managing director at Dell Technologies Capital, said Ascerta is building the system of record for AI value creation.

CEO David Tepper said the market is full of vanity metrics and companies need business-specific insights to prevent waste and optimize for value.

The company will use the capital to scale its platform and go-to-market team and extend integrations across the enterprise AI stack.