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Should You Build or Buy AI Agents for Your Finance Team?
Should your team build custom AI agents or buy proven solutions? We break down costs, timelines, and outcomes to help you decide.

Co-founder & CTO
Timmy spent seven years as a nuclear submarine officer in the US Navy and taught cybersecurity at the Naval Academy, then built AI to automate bank operations at a fintech startup. He has two computer science degrees from MIT, an MBA from Harvard Business School, and a patent on data algorithms.
Should your team build custom AI agents or buy proven solutions? We break down costs, timelines, and outcomes to help you decide.
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We’re going to show you how bringing AI into your ERP system can help your AR team work smarter (not harder), cut down on those tedious manual tasks, and probably get you paid faster too.
Managing invoices isn’t what it used to be, since companies are moving away from manual data entry and error-prone matching processes, all thanks to AI invoice matching systems.
This article will show you how modern AR automation addresses these challenges (compared to legacy AR processes), giving your team the tools they need to work smarter and get paid faster.
In today’s economy, getting more reliable cash flow predictions is worth its weight in gold. Let’s evaluate in detail how that can be done.
You don’t need to rebuild your entire financial infrastructure to bring AI into your AR processes.
AR automation transforms manual processes into efficient workflows — understand how it works and why finance teams are switching.
Bring a batch of your real AR — invoices, payments, whatever’s messiest — and we’ll show you exactly how the agents would read, match, and post it back against your own records.