Hi there and welcome to Funded, where we spotlight the early-stage bets on the future of tech.

This week, we’re looking at infrastructure for finance teams finally catching up to the complexity of modern B2B business models, and what it takes to make AI actually usable in that stack.

Zenskar raised a $15 million Series A led by Susquehanna Venture Capital, Bessemer Venture Partners, Shine Capital, and Rho to expand its agentic billing and revenue automation platform.

Zenskar is going after a stubborn problem: billing systems that break under real-world complexity. Modern B2B companies operate across usage-based pricing, prepaid credits, multi-entity structures, and constant contract changes. Most teams patch this together with workarounds or internal tools, creating risk across revenue recognition, compliance, and collections. Zenskar’s pitch is simple but ambitious: rebuild the system from the ground up so AI can actually work on top of it.

The company’s approach centers on an agentic architecture. Its growing Agents Marketplace lets finance teams create and deploy workflows across the entire order-to-cash cycle without engineering support. Agents can handle billing, flag exceptions, and even execute approvals through tools like Slack. The underlying system models contracts as flexible data objects, allowing teams to adapt to edge cases without rewriting logic every time the business changes.

“Finance teams aren’t struggling because they lack AI tools. They’re struggling because the systems underneath those tools were built for a simpler world,” said CEO Apurv Bansal.

That framing seems to be resonating. Zenskar reports 5x revenue growth over the past year, with customers seeing tangible operational gains, from faster billing cycles to earlier collections and quicker financial closes. In some cases, companies are scaling without adding headcount or replacing years of internal infrastructure.

The takeaway is less about AI features and more about foundations. Zenskar is betting that finance won’t meaningfully adopt AI until the systems beneath it are rebuilt for flexibility, auditability, and constant change. If that’s right, the next wave of fintech won’t just automate workflows, it will redefine the data layer those workflows depend on.

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This article was drafted with the help of generative AI using company-submitted details, then manually edited and carefully reviewed by a human editor before publication.