AI Embedded in Finance Workflows
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Geoff Charles, VP of Product at Ramp, on Ramp's AI flywheel
AI should be more than a flashy chatbot interface: it should be embedded in your workflows to actually get things done.
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The real product advantage is not having an AI chat box, it is owning the work step where money moves and decisions get made. In Ramp’s world that means reading receipts, invoices, and contracts inside the normal finance flow, then surfacing the one action that matters, like confirming a minibar charge, flagging a bad policy exception, or teeing up a contract cancellation email before renewal hits.
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This is a shift from request and response software to exception handling software. Instead of a finance team uploading a contract and asking follow up questions, Ramp wants the system to ingest the file, pull renewal terms, connect them to vendor payments, and alert only when a human decision is needed.
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The economic point is margin expansion. Ramp describes LLMs as making unstructured finance work cheap enough to automate, especially tasks that previously depended on OCR vendors or manual review. That lets spend management move beyond interchange funded cards into higher value software around AP, procurement, and vendor negotiation.
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A useful comparison is BRM, which also treats AI as a worker inside vendor management, not just a chat layer. BRM builds a vendor record from email, ERP, identity, and contract systems, then runs agents for renewals, pricing checks, and compliance. The common pattern is that the winning product is the system of action wrapped around the data.
This pushes finance software toward autopilot. The companies that win will be the ones with permission to sit inside approvals, payments, contracts, and policies, because that is where AI can quietly remove labor and compound into a broader back office platform over time.