The ERP has the records.
Your team connects the dots.

Payment reconciliation

Match settled payments with the right invoice or settlement record. Keep partial payments, fees, duplicates and unidentified receipts distinct.

Cash application

Propose allocations from remittance evidence, validate against current open balances and apply only within approved matching policy.

Collections coordination

Assemble overdue balances, disputes and promises to pay. Suppress inappropriate follow-ups when a payment is pending or an invoice is disputed.

Invoice exceptions

Resolve missing references, PO mismatches or approval gaps. Route an actionable case to its owner rather than sending another unstructured email.

These are separate process boundaries. We start with one, establish its baseline and connect adjacent steps only where they affect the outcome.

We design around your controller’s policies. Automation does not establish accounting policy, authorize money movement or replace financial review. The system records which rule, evidence and person authorized the action.

The matching decision and the ERP update are different states. If an API times out after posting, the workflow must check whether the update already happened before trying again.

We define stable transaction keys, source lineage, synchronization timing and recovery behavior. Bank settlement date, invoice date and posting date remain distinct. A late file or a reopened invoice should trigger a controlled reassessment, not silently overwrite the decision history.

Where native ERP or reconciliation features cover the workflow, configuring those features may be the better choice. Custom work is justified by the remaining handoffs, exception logic or missing system connections.

• Manual effort: touches and active minutes per transaction, split between normal cases and exceptions.
• Cycle time: receipt-to-application time and age of the unresolved queue.
• Quality: false matches, incorrect postings, reversals and repeated investigations.
• Economics: processing and review costs per transaction, including tooling and ongoing maintenance.

Days to cash can matter in collections, but payment terms, disputes and customer behavior also affect it. We do not attribute every change to automation.

A high exception rate may signal broken upstream data rather than an AI opportunity. The baseline needs to distinguish missing information, legitimate exceptions and avoidable process errors.

We map the path with the finance owner and the people doing the work. We agree the matching policy, approval authority, data access and representative test cases before proposing a build.

The first release can prepare recommendations in shadow mode while your team keeps control of posting. We compare outcomes and review effort, then expand the approved boundary only when the evidence supports it.