AI agents for invoices, quotes and reporting
A business-process agent prepares a piece of work that today takes a person hours, and hands it over for a decision: an incoming invoice matched against the order and the delivery note, a quote drafted from ERP data and the customer's history, a reply to a customer inquiry with context from CRM and stock, the month-end pack with links to the source data. The agent prepares, a person approves, the audit trail records it. We build the first two processes in a six-week pilot, measured against the manual baseline, in your ERP, not in a demo system.
Four processes we start with, and what each needs from you
- Incoming invoices: the agent compares the invoice with the purchase order and the delivery note, prepares the posting and presents the exceptions for approval. Needs: read access to purchase orders and goods receipts, a mailbox or scanner feed, the exception rules your AP team uses today.
- Quotes and price lists: from ERP data and the customer's history it drafts a quote including margin; the salesperson adjusts and sends. Needs: price lists, cost data, three months of past quotes to learn your format.
- Customer communication: replies to inquiries with context from CRM and from stock, in your company's tone, ready to send; nothing is sent without a person. Needs: CRM read access, stock availability, ten examples of replies you are proud of.
- Reporting and month-end close: monthly packs, variance checks and management overviews, produced automatically with links to the source data. Needs: the current pack as a template and read access to the general ledger.
- Every write to the system is an allowlisted call with a person's confirmation in the audit log; on SAP the licensing position for indirect use is confirmed with your SAP account team before production.
Why the agent never acts alone
Real value does not come from a chat window. It comes when the AI layer is connected to your systems and can read data and trigger actions in SAP, ERP, CRM and documents. That connection runs through MCP, an open protocol, and it comes with two rules we do not negotiate: every agent inherits the permissions of the specific user, and every write into a system is approved by a person. The audit trail shows the source data, the model and version, the proposed action, who approved it and what changed.
Where we begin
We begin with processes where the investment returns within about 60 days: high volume, clear rules, a person already doing the checking by hand. In the assessment we pick two to four of them, agree the measures with the process owners, and build the first agent on real documents from your systems.
Questions we get asked
Which systems can the agents connect to?
SAP in both S/4HANA and ECC, ERP and CRM systems, Microsoft 365 and Google Workspace, e-mail and calendar, databases and internal APIs, document management systems. The connection runs through MCP connectors we build and govern.
What if the agent gets it wrong?
A wrong proposal is rejected by the approver before anything changes in the system, and the rejection is recorded. That record is what we use to improve the agent. No write happens without a person.
How do we measure whether it paid off?
By cycle time, throughput, quality and the capacity returned to the team, agreed with the process owner before the build and reported monthly.
Does this need a new interface for our people?
No. Approvals happen where people already work: in the ERP task list, in e-mail or in the collaboration tool you use. The agent adapts to the process, not the other way round.
Talk to us.
A 30-minute conversation on your scenarios. The call and the written assessment you leave with are free, whether we work together or not. The next step, if there is one, is a fixed-price six-week pilot in your environment with no obligation to continue.
Or write to us directly: info@iteractive.ai · +421 905 452 325