AI Services
They partnered with RapidDev to rebuild accounts payable from the ground up as an AI-powered, self-improving system.
About
A $30M construction company operating across 6 locations with 120 field crews was drowning in paper. Thousands of invoices flowed in every month from suppliers, subcontractors, equipment rentals, and fuel vendors. And every one of them was processed by hand. Despite the size of the operation, the finance function was running on manual data entry, gut-feel approvals, and quarterly audit catch-ups.
The Challenge
The company's AP operation looked busy, but underneath the activity was a business quietly bleeding money and visibility.
3,500 invoices a month, all processed manually. Invoices arrived as PDFs, emails, photos, and paper, no two formats alike. Four full-time AP staff spent their days keying data into QuickBooks, matching purchase orders, and chasing approvals. Payment cycles dragged 12 to 18 days. Slow processing meant the company consistently missed early-pay discounts, costing roughly $85K a year in money left on the table. Duplicate invoices were costing $120K annually. Without a system to cross-reference incoming invoices against history, duplicates only surfaced during quarterly audits, long after the money had gone out the door. The CFO was forecasting cash flow on guesswork. With no real-time view of AP commitments, financial planning was reactive at best. Leadership couldn't see what was owed until it was already overdue.
The Solution
Every invoice, regardless of how it arrives (email, upload, photo scan, vendor portal), is funneled into a single intake pipeline. From there, an AI classifier trained on 18 months of the company's own historical data determines whether each document is an invoice, statement, receipt, or junk.
OCR and LLM extraction pull out vendor, amount, line items, PO, and date into clean structured data. Anomaly detection cross-references prior invoices and open POs to flag duplicates and mismatches before they cost the business money. Invoices under $500 are auto-approved; anything larger is routed to the right site manager for sign-off. And the CFO, for the first time, sees AP commitments, aging, and cash flow impact in real time as invoices process.
The result is an AP function that runs itself with humans focused on judgment calls, not data entry.
What Makes it Different
We helped build a smarter AP system that improves with every correction and scales without extra headcount.
A system that gets smarter every month.
Every time AP staff corrects an error or overrides a flag, that decision becomes new training data. The model compounds in value over time: auto-classification accuracy went from 78% in month one to 97% by month six, and auto-approvals climbed from 35% to 74%. The longer the company runs it, the more money it saves.
Built on the company's own data, not a generic model.
The classifier was trained on 18 months of the business's historical invoices, so it understands their specific vendors, formats, and edge cases from day one, something off-the-shelf AP tools can't deliver.
Anomaly detection that prevents losses before they happen.
Instead of catching duplicates and PO mismatches during quarterly audits, the system flags them in real time. This single capability eliminated $120K a year in overpayments.
The Result
- AP headcount: 4 → 1. Three staff redeployed from data entry to vendor management, where they actually drive business value.
- Processing time: 12-18 days → 2-3 days. Invoices move at the speed of business, not the speed of paper.
- Duplicate payments: $120K/year → $0. The leak is closed.
- Early-pay discounts: $85K/year recovered. Money the business was leaving on the table is now flowing back to the bottom line.
- $350K+ in annual value delivered by the system. Real, measurable ROI from month one.
- Two new locations added without new AP hires. The system scales with the business, not against it.
As the CFO put it: "We didn't just automate invoice processing. We built a system that understands our invoices better every month."
That's the difference between buying software and building an asset, and it's what turned a back-office bottleneck into a compounding strategic advantage.
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