AP Invoice Automation700+ Invoices. Zero Manual Work.
A West Coast manufacturing company was processing 700 to 800 invoices per week entirely by hand, with 5 to 6 team members touching every invoice before it posted to their ERP. We replaced that with an AI pipeline deployed in 12 weeks. The finance team now handles exceptions only.
The Problem
The company's AP team received all invoices through a single email inbox. Each invoice required manual download, review, GL coding, PO matching against their ERP, and verification against scale records for commodity vendors. Five to six people touched every invoice before it posted.
At 700 to 800 invoices per week, the team was entirely consumed by data entry. They had no capacity to catch anomalies, audit vendor patterns, or handle finance work that required judgment.
- 700–800 invoices per week, all arriving via AP email inbox
- 5–6 manual touchpoints per invoice
- GL coding done by hand from memory and reference sheets
- PO matching required manual ERP lookup
- Commodity vendors required cross-reference against scale records
- Paper invoices required manual scanning and routing
The Result
The AP pipeline monitors the inbox continuously and processes each invoice automatically. GL codes are applied by rule, POs are matched, quantities are verified, and the invoice posts to the ERP without any manual work. Exceptions are the only invoices the team touches.
The system runs on the client's own AWS infrastructure. They own all credentials, code, and configurations. It operates independently regardless of CalTech Web's involvement.
- AP inbox monitored and processed automatically
- GL coding applied by rules engine, no manual input
- PO matching and quantity verification fully automated
- Exceptions routed to the right person with full context
- Every invoice action logged with a full audit trail
- 100+ invoices can process simultaneously, no bottlenecks
How It Works Under the Hood
The system runs entirely in the cloud. The client owns all credentials, logins, and access. If CalTech Web is unavailable, the system continues operating independently.
Invoice Processing Pipeline
Invoices that fail GL coding, PO matching, or amount verification are flagged and routed to the right team member for review. Repeated exceptions trigger new rule-building.
AWS EC2. All processing, logging, and temporary storage runs here. The client owns all admin credentials.
Cron-based job polling every 5 seconds. Each invoice spawns an independent agent session, allowing 100+ invoices to process simultaneously with no bottlenecks.
Primary: EDI flat file via data profile architecture. Fallback: browser automation for post types not covered by the EDI profile.
Automated extraction from the scale records system to cross-reference weights against commodity invoices, eliminating a manual lookup step.
All invoice data, logs, and extracted files are stored in the client's AWS environment. No data transits third-party AP platforms.
Custom Build vs. Off-the-Shelf AP Software
Platforms like Tipalti, Bill.com, and Coupa solve parts of the problem. A custom build owns the whole workflow.
Invoice data stored on the vendor's servers. Subject to their retention and access policies.
All invoice data, logs, and extracted files stay in your AWS environment. No third-party access.
Per-invoice fees or a percentage of spend. Costs scale indefinitely as volume grows.
One-time build fee. Flat monthly retainer. Costs are fixed regardless of invoice volume.
Coding logic lives inside the platform's rigid mapping interface. Limited to their data model.
Rules are built to match your exact GL structure, cost centers, and ERP posting logic.
Switching platforms requires full re-onboarding, data migration, and re-training.
You own the code and credentials. The system runs independently of CalTech Web.
12 Weeks from Kickoff to Full Go-Live
Built in three phases so the AP team runs their normal process in parallel before any cutover. Errors surface before go-live, not after.
Workflow audit with the AP team. Document all coding rules, PO structures, and ERP data profiles. Collect sample invoice sets. Provision AWS environment.
Build inbox monitor, OCR pipeline, GL coding engine, and PO matching for the top-volume vendors (70% of weekly invoice load). Configure ERP connector and exception routing.
Automated process runs alongside manual process using live invoices. AP team surfaces any errors. Buffer for edge cases and ERP integration adjustments.
Extend automation to remaining vendors. Build cross-reference logic for variable-price invoice matching. Test in parallel with Phase A running live.
Full AP team training. Phase B go-live. Written SOPs and recorded walkthroughs delivered.
Ongoing exception rule-building, new vendor templates, and ERP refinements. Additional automations added as capacity frees up.
This Engagement
AP automation at this scale is priced as a one-time build fee plus a monthly retainer for ongoing support, exception rule-building, and optimization.
- Inbox monitor and OCR pipeline
- GL coding rules engine
- PO matching and 3-way verification
- ERP EDI connector and fallback automation
- Exception routing with full audit trail
- Training, SOPs, and handoff documentation
- Exception rule-building as new patterns emerge
- New vendor template additions
- ERP configuration updates
- System monitoring and uptime oversight
Based on California market data: 4 AP staff freed from manual processing at an average fully loaded cost of $75,000/yr each (base salary ~$58K plus benefits and payroll taxes).
Is AP Automation Right for You?
This solution is a strong fit if your team processes a high volume of invoices through a consistent channel (email, portal, or scanner) and the manual work is eating into finance headcount.
- 100+ invoices per week, any volume
- Invoices arrive by email or document scanner
- Consistent vendor set with repeatable formats
- ERP that accepts EDI flat files or has an API
- Finance team spending significant time on data entry
Want to Build Something Like This?
Every build starts with a 30-minute scoping call. Tell us the workflow, we'll tell you if it's a fit.