RightRev, the AI revenue platform for finance teams, defined five requirements the revenue number must meet before finance can trust it to AI, and launched new AI agents built to meet them with minimal manual work from finance. To be audit-ready as pricing and systems keep changing, revenue in the rapidly maturing AI economy must:

• Connect every revenue data source and continuously reconcile with billing, ERP, and contract data in real time.
• Work alongside the ERP and existing finance systems, with IT as a partner.
• Keep pace with new pricing models, so the business launches on time and finance is ready on day one.
• Maintain continuous revenue close, so the number is reconciled throughout the period and close confirms it, instead of discovering what's wrong with it.
• Be auditable down to the performance obligation, with visibility into every change that touched it, however small.

"AI is accelerating the shift toward consumption-based pricing, making revenue increasingly complex to calculate and recognize," said Jagan Reddy, RightRev founder and CEO. "With usage-based, prepaid, and hybrid contracts, revenue can change with every customer transaction. But finance still needs to account for every dollar and explain exactly how it was calculated. RightRev keeps revenue tied to the underlying contract, applies the rules consistently as pricing changes, and maintains a clear audit trail that finance teams can stand behind."

Jagan has issued additional guidance on how organizations can adapt revenue recognition for variable pricing. He will also discuss why revenue truth has a data problem and how to fix it at the Finance and Accounting Technology Expo in New York City on November 18.

RightAgents empower finance teams to meet these requirements with minimal manual work. They pull terms from contracts, turn revenue policies into rules, reconcile across systems, and draft the explanations. A person reviews and approves the result.

RightRev AI Activates Agents to Generate Audit-Ready Revenue Truth
RightRev processes more than $44 billion in annual customer revenue, and its revenue engine derives each number from the contract by rule. RightRev AI builds on that foundation with RightAgents, the first suite of AI agents dedicated solely to the revenue number, covering usage, consumption, credit, prepaid drawdown, and hybrid contracts.

RightAgents address the repeatable work of setting up, checking, and explaining the revenue number, so finance teams get there with minimal manual touch. The number stays with the controllers and revenue accountants who answer for it.

RightContext is the data and context layer of the platform. It connects to any billing system, ERP, or usage source, normalizes the input, and automatically builds context around it. Finance teams can also define their own context so the people who know the business decide how the data is read. That context is applied the same way every time and can be relied on by the engine, RightAgents, and any AI tool connected through Model Context Protocol (MCP).

The revenue engine calculates revenue from that context using each customer's own policies. RightRev AI agents run on that derived revenue number and pull terms from new contracts, send changes back through the engine, and flag anything that doesn't reconcile before it reaches the general ledger. Every journal entry traces back to the contract, data, and rule behind it, and a person approves everything before it posts.

"Revenue is the number every other number in finance is built on. Forecasts, planning, the board deck, and every AI workflow that touches them inherit it, so the order matters. RightRev is built for this reality. Data from every system comes in and gets checked, the revenue number is calculated by rule with every entry traced to its contract, the agents work against that number, and finance approves what reaches the ledger. The agents handle the gathering, matching, and drafting, so finance's time goes to review and approval. AI will run more and more of finance, and it will only be as right as the revenue number underneath it," said Jagan.

Each agent takes over a piece of the work finance teams do by hand today:

• Anomalies: Watches contracts and revenue schedules for anything unusual, such as unexpected variances, missing prices, or odd allocations, and flags it for review.
• Contract Checklist: Pulls the key terms and obligations from each customer contract and checks them against an ASC 606 checklist or an organization's own checklist. A reviewer signs off, and the documentation is ready for the audit file.
• Revenue Assistant: Answers natural-language questions about contracts, revenue, and balances using the organization's revenue data.
• Architect: Creates rules for a policy or use case, such as tiered pricing or breakage. The team approves it before it goes live, and it then runs the same way every time, with no code.
• Use Case Modeling: Works out the scenarios each customer's setup has to handle, builds the tests, and runs them, so changes are checked before they reach the books.
• Flux: Explains why revenue and balances moved from one period to the next, ties each change to the contracts behind it, and drafts the commentary for sign-off.
• Reconciliation: Checks that revenue matches across source systems, RightRev, and the general ledger, explains each difference, and packages it for review and sign-off.

When the business launches new pricing, Architect drafts the rule from a plain-English description, finance approves it, and it runs the same way every time. All RightRev AI agents are available through MCP, so teams can run them from Claude, ChatGPT, and other AI tools within each person's existing permissions.