SaaS companies now sell in far more complicated ways than they used to. Contracts mix subscriptions, usage-based fees, prepaid credits, minimum commitments, overages and custom discounts. More and more products also have AI built in, so customers are paying for tokens and API calls, which squeezes margins. Many finance and accounting teams can’t keep up. They end up running billing, revenue recognition, collections and reporting on spreadsheets or on homegrown systems that take up engineering time. AI revenue automation fixes this by turning signed contracts and raw usage data straight into accurate invoices, ASC 606 and IFRS 15-compliant revenue schedules, and journal entries ready for the ERP.
In this segment, Apurv Bansal, Co-Founder and CEO of Zenskar, showed how the company’s AI-native revenue automation platform sits between a business’s CRM and its ERP and handles everything in between: metering, billing, collections, revenue recognition and analytics. Bansal explained that Zenskar spent more than three years building a patent-pending, graph-based data model. That model is the foundation that lets AI agents handle complex contracts reliably while respecting accounting rules. The live demo followed a contract from start to finish. An AI agent read the contract and pulled out the pricing terms, usage data was brought in and aggregated, invoices were created, performance obligations were identified, and transaction-level journal entries were produced.
The session ended with a Q&A moderated by Kevin Appleby. Topics included billing for AI token consumption, keeping a single source of truth between Zenskar and the ERP, and handling contract changes mid-term. The main message was what Zenskar calls “zero-touch finance”: companies can grow revenue without growing their finance teams at the same rate. That frees staff for strategic work, speeds up collections and moves the monthly close toward day zero.
Highlights:
- Zenskar positions itself as an AI-native revenue automation platform that connects CRM and ERP systems and offers metering, billing, collections, revenue recognition and analytics as separate modules that can be used alone or together.
- An AI agent reads uploaded or CRM-synced sales contracts in real time and extracts the billing and revenue terms. It supports a wide range of pricing models, including tiered, volume, percentage, prepaid, postpaid and minimum-commitment pricing.
- Usage data can come in through API, CSV upload or more than 200 data warehouse connectors, and it can be aggregated with standard functions or custom SQL. Because metering is built separately from billing, token- and API-based AI pricing works natively rather than as an afterthought.
- Billing and revenue recognition run independently. Zenskar acts as an ASC 606 and IFRS 15-compliant revenue subledger, identifies performance obligations, and syncs transaction-level journal entries to the ERP both ways, so the ERP stays the system of record.
- When a contract changes, whether an upsell, a downsell or a mid-cycle change, Zenskar treats it as a new version and automatically recalculates the billing and revenue schedules end to end.
- A conversational reporting agent, also available in Slack, turns plain-language questions into SQL for instant answers on metrics like MRR, ARR, churn, top customers and aging. Customers report faster collections, less revenue leakage, and month-end closes reaching day one or day two.
