A general-purpose AI agent will happily attempt your month-end close. The question a CFO has to answer is what happens on the run where it is confidently wrong, and whether anyone would be able to tell.
A generic agent decides by inference. It is impressive, fast and very hard to audit, because the reasoning behind any given action is not written down anywhere you can read. A Pantera keeps the rules explicit, stops at the edges of what it was authorised to do, and stores the rule it applied with every action. In regulated finance, that difference is the entire product.
Open-ended work where being roughly right is useful and a person reviews the output anyway: research, drafting, summarising, exploring a dataset, prototyping an idea quickly.
Finance operations where an error is not a bad draft but a wrong journal entry, a missed filing or a payment that should not have gone out, and where someone will eventually ask you to prove what happened.
A summary that misses a nuance costs a few minutes. A reconciliation that quietly matches the wrong transaction costs a restatement, and it may not surface until the audit.
Auditors and regulators do not accept that the system decided. They want the rule, the evidence and the person who approved the exception. That has to exist before the question is asked, not be reconstructed after.
A Pantera is not built to replace the approval. It is built to do the work up to the approval, hand over a clean decision, and record what happened on both sides of it.
For analysis, drafting, research and anything exploratory, a general-purpose agent is excellent and we use that class of tool ourselves. The line we draw is execution in production over financial systems, where the output is an entry and not a suggestion.
If you are evaluating one for a close, the useful test is simple: ask it to show you the rule it applied and who approved it. The answer tells you which category you are in.
Yes. It uses AI to understand the process you recorded and to read the documents it has to work with. It does not use inference to decide whether a transaction matches. That is a rule, and the rule is written down.
Explicit limits, mandatory approvals on the actions you choose, scoped system access, and a full record of every step, which makes anything unexpected visible rather than silent.
No. A copilot helps a person do the work and the person still executes it. A digital worker executes the process and brings a person in for the decisions that need one.
Plans start at USD 399 a month plus an implementation fee, with the cost per execution published on the pricing page.
Record one process the way you run it today and we will show you what a Pantera does with it.
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AI digital workers that execute finance operations on the systems you already run.
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