RegalBizNet OS Purchasing: AI agents that work inside your ERP

Late purchase orders rarely come out of nowhere. The data was sitting in your ERP the whole time; nobody caught it early enough to do anything about it. In this short demo of RegalBizNet OS Purchasing, Ana runs purchasing with a team of AI agents that watch open POs, flag the problem and bring her a recommendation she can approve in one step.

In the video: Ana and her ERP (0:00) · the agents catch a late order (0:16) · approve once, written back to the ERP (0:35) · RegalBizNet OS Purchasing (0:49).

For most buyers, the day starts the same way: pull the open-PO report, email vendors for updates, check stock in a spreadsheet and get on the phone to expedite. The ERP has the information, but it doesn't raise its hand or suggest a next step. So a late delivery usually surfaces when the part is already missing.

The scenario is fictional. The workflow is the point.

1. Catch the risk

The agents notice that PO-4821 is four days late and that, without it, the part stocks out on Friday.

2. Compare the options

They line up three paths: expedite with the current vendor, switch to an alternate vendor or reschedule production. Their pick is the alternate vendor: same part, delivered Thursday.

3. Approve once, write it back

Ana reviews the recommendation and approves it once. The agents create the new PO in the ERP, update the production schedule and give the warehouse a heads-up. She makes the call; they handle the data entry.

• PO tracking: watches due dates and inventory levels and raises the flag.
• Vendor sourcing: compares alternatives and builds the recommendation.
• ERP update: writes approved changes back into the system.

Splitting the work this way is practical: each agent only gets the permissions its job needs, and it's always clear who did what.

The demo shows the workflow on SAP, Oracle or Microsoft Dynamics. The goal isn't a rip-and-replace; switching ERPs is expensive and risky. It's to put AI agents to work next to the system you already have. How they connect depends on your ERP and the access it allows, and we work that out during the diagnosis.

Hypothetical scenarios, not customer stories:

• Hardware store or building-supply dealer: a seasonal SKU dips below its reorder point. The agent sends an alert and drafts a PO for someone to approve.
• Restaurant group: the agent compares ingredient usage against open supplier orders and warns you before you run short for the weekend.
• Car dealership: a back-ordered part is holding up a service appointment. The agent suggests alternatives and, once the service advisor signs off, reschedules the customer.

• Start with what you have. We review your ERP, your purchasing workflow and who approves what.
• Approvals based on risk. Together we decide what can flow through and what needs a yes. New POs and new vendors always go to a person.
• Least-privilege access. Each agent only touches the data and actions its task requires.
• Parallel run. The agents work alongside your system, without touching production, until you've compared results and decided.
• Audit trail. Every action an agent takes is logged and reviewable.

If your buyers spend more time chasing POs than making decisions, take a look at process automation and our industry apps. New to the idea? Start with what agentic AI is. To walk through your purchasing workflow and your ERP, request your diagnosis.

Where we serve: the US, LATAM and Spain.

AI built in, not bolted on. Enhances your ERP. Doesn't replace it.

About the author. César Cevallos, Founder at RegalBiz.Net. He designs and implements AI agents and automations for small and midsize businesses and organizations in the US, LATAM and Spain, and works with companies as a Fractional Chief AI Officer. LinkedIn

*Reviewed by César Cevallos: Oct 31, 2026.*