Zenskar, an AI-native billing and revenue automation platform, this week announced a $15 million Series A led by Susquehanna Venture Capital, Bessemer Venture Partners, Shine Capital and Rho, with participation from Rocketship, J-Ventures, Future Back Ventures by Bain & Company, and Converge. The funding will expand Zenskar’s agentic capabilities.
Zenskar was built to solve revenue automation for the complex pricing and business models of modern B2B companies through an AI-native approach. The Series A funding enables Zenskar to expand its agentic capabilities, including its Agents Marketplace — a library of agents that finance teams can create, customize, chain, and deploy across the full order-to-cash cycle without engineering involvement. Their Slack agent and MCP that connects with major AI tools like Claude, ChatGPT, etc. allows teams to assign tasks, review exceptions, and approve actions from wherever they work.
“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 Apurv Bansal, CEO and co-founder of Zenskar. “Bolting AI onto these broken foundations preserves their limitations, so we built an entirely new architecture, one that can truly free finance from their operational grunt work so they can focus on strategic work.”
With usage-based tiers, prepaid credits, amendments, minimum commitments, customer hierarchies, multiple entities and multiple currencies, workarounds create cascading risks, including revenue leakage, delayed collections, and audit and compliance issues.
“Finance teams have lagged in AI adoption because accuracy, auditability, and compliance are non-negotiable. Legacy systems treat complexity as an exception, not the norm — forcing teams into costly, error-prone workarounds and making any AI built on top of them unreliable. Zenskar’s flexible foundation is what lets AI deliver on its promise,” added Sai Araveti, an investment advisor at Susquehanna.
“The problems that break finance teams aren’t the obvious ones, but the complex ones like bespoke pricing structures that are dynamic, AI token consumption that changes each time a new model drops, or ASC 606-compliant revenue recognition that needs to be closed in a day,” said Anant Vidur Puri, a partner at Bessemer Venture Partners. “What makes Zenskar different is that their AI-native, agentic architecture was built exactly for this and to make sure a developer is not required anytime something changes.”
Zenskar models contract data as objects on a graph — covering every amendment, every usage model, every edge case. This is paired with rule-based calculations and purpose-built AI.