We spoke with Nominal about a different approach to that capacity problem: using AI agents to execute accounting workflows rather than simply helping teams manage them.
For someone hearing about Nominal for the first time—what do you actually do, in plain English?
Nominal deploys AI agents that execute accounting workflows such as transaction matching, reconciliations, and close activities across entities. The agents operate on top of existing ERP systems and complete the underlying work, with accountants reviewing and approving outputs before they are finalized.
What’s breaking (or slowing down) for finance teams today—and why is it becoming harder to ignore?
Accounting workload tends to scale with business complexity. More entities and transactions mean more balances to reconcile, more intercompany activity to match, and more information to analyze before finance can produce a reliable set of numbers.
That becomes particularly challenging for businesses growing through acquisitions or geographic expansion. Adding accounting headcount at the same rate isn’t always practical, which creates a capacity problem: how does the team absorb more work without allowing the close to stretch further? Nominal’s approach is to have agents execute recurring workflows continuously, rather than allowing that work to accumulate at period-end.
Who tends to get the most value from this—and where does it typically click fastest?
Multi-entity complexity is often the defining factor. Nominal is designed for larger organizations—typically from $100 million to $10 billion-plus in revenue—where accounting teams may be working across multiple entities, ERP instances, and high transaction volumes.
The operational pain is usually felt first by Controllers, Directors of Accounting, and financial operations teams responsible for getting the books closed. CFOs and finance transformation leaders may look at the same challenge more broadly: whether the accounting operating model can continue scaling as the business adds entities and complexity.
If a finance team started using your approach tomorrow, where would they feel the impact first?
Intercompany reconciliation is a natural starting point. Instead of waiting until period-end to identify mismatches, agents can match balances across entities and systems throughout the month, reducing the back-and-forth that often slows the close.
The same execution model can extend to balance sheet reconciliations and flux analysis. Supporting evidence and transaction-level explanations are documented as the work happens, changing audit preparation from an exercise in reconstructing what happened months earlier into more of a review of an existing trail.
How does this fit into the existing finance tech stack—and how does it hold up as the business grows?
Rather than replacing the ERP, Nominal connects with systems such as NetSuite, SAP, and Oracle, reads the underlying transaction data, and writes approved outputs back into the system of record. Human approval remains part of the workflow before actions are finalized.
As organizations acquire subsidiaries, enter new markets, or add ERP instances, the idea is for agents to absorb more of the resulting accounting workload. Nominal describes this model as Agentic Performance Management (APM): specialized agents coordinating across multi-step accounting processes with traceability and human oversight. The distinction is less about giving accountants another place to manage tasks and more about shifting recurring execution work from the team to the system.
Explore More at the Finance & Accounting Technology Expo (FATE) 2026
Meet Nominal at FATE 2026 (Nov 18–19, NYC)—a curated, high-signal environment where finance teams can compare solutions side-by-side, see how real workflows operate, and evaluate what fits their business.
