Automate Your Accounting Department with Custom AI
The cost to optimize a small business accounting department is a fixed-price project, typically lasting 2 to 4 weeks. This one-time build replaces recurring software fees and manual data entry with a system you own completely.
We built an invoice processing system for a 25-person construction firm handling 400-500 vendor invoices per month. Their bookkeeper's manual entry time dropped from 6 minutes per invoice to an 8-second review, saving them over 35 hours per month.
The timeline depends on the number of document types (invoices, receipts, POs) and the complexity of your approval rules. A business processing 300 monthly invoices from 10-15 vendors into QuickBooks Online is a standard 3-week build.
What Problem Does This Solve?
Many accounting departments start with a subscription to an OCR service like Nanonets or Rossum. While these tools extract text, they struggle with non-standard invoice formats from smaller vendors. This forces a bookkeeper to manually verify every single line item, correcting errors like 'l-beam' being read as '1-beam'. The OCR only handles 60% of the work, but you pay for 100% of the processing.
Next, they try dedicated AP platforms like Bill.com. These platforms solve the payment workflow but introduce their own data silos and high per-transaction fees. Getting invoice data back into your ERP or project management tool requires another fragile integration. A 20-person agency paying $79/month plus transaction fees still spends hours exporting CSVs to match project costs in their system.
These off-the-shelf tools fail because they treat accounting as a generic workflow. They cannot handle industry-specific logic, like a construction company needing to match a supplier invoice against a purchase order and a specific job number before approval. The rigid rulesets mean exceptions always require manual intervention, which is where all the time is lost.
How Does It Work?
We start by connecting directly to your email inbox or document source via API. Using the Claude 3 Sonnet API, we build a classification and extraction pipeline in Python. The model is trained on just 20-30 examples of your specific invoices, learning to identify fields like 'Invoice Number' and 'Due Date' regardless of layout. Scans are processed at a minimum of 300 DPI for character recognition.
The core logic is a FastAPI service that orchestrates the workflow. Once Claude extracts the data into a JSON object, the service validates it against your business rules. For a logistics client, we cross-referenced extracted PO numbers against their live inventory database in Supabase. Mismatched or missing POs are flagged and sent to a specific Slack channel for review, while valid invoices proceed automatically. This entire process takes under 8 seconds per document.
The FastAPI service is deployed as a serverless function on AWS Lambda. This architecture is event-driven, meaning it only runs when an invoice arrives, keeping costs extremely low. For a client processing 1,000 documents per month, the combined AWS Lambda and Claude API costs are under $30/month. We write the extracted data directly to QuickBooks Online or your ERP via their native API, ensuring a 200ms response time for data sync.
We configure structured logging with structlog and alerts for any processing failures. You get the complete Python source code in your private GitHub repository, along with a runbook explaining how to update vendor-specific rules. The final system achieves over 99.5% field-level accuracy, which we verify during a 2-week post-launch monitoring period.
What Are the Key Benefits?
From Manual Entry to 8-Second Review
Reduce per-invoice processing time by over 95%. Your team shifts from tedious data entry to high-value review of flagged exceptions.
Pay Once, Own It Forever
A single fixed-price project replaces monthly per-user SaaS fees. You receive the full Python source code and can modify it as your business grows.
Your Code, Your GitHub Repo
We deliver the complete, production-ready codebase to your GitHub account. No vendor lock-in, no black boxes, no proprietary platforms.
Alerts For Failures, Not Successes
We configure alerts in Slack or email that trigger only when an invoice fails validation. No more sifting through dashboards to find problems.
Connects Directly to Your ERP
We use official APIs to integrate with QuickBooks, NetSuite, or industry-specific platforms. Data syncs instantly without manual CSV uploads.
What Does the Process Look Like?
Week 1: Scoping and Access
You provide 20-30 sample documents and read-only access to your accounting software. We map your current workflow and define the precise business rules for automation.
Week 2: Core Pipeline Build
We build the extraction and validation logic using the Claude API and FastAPI. You receive a demo link to test the system with your own sample documents.
Week 3: Integration and Deployment
We connect the pipeline to your live systems (email, ERP) and deploy it on AWS Lambda. You receive the full source code in your GitHub repository.
Weeks 4-5: Monitoring and Handoff
We monitor the live system for 2 weeks to ensure accuracy and handle any edge cases. You receive a final runbook with operational instructions and maintenance steps.
Frequently Asked Questions
- How does the final price vary for a 2 vs 4-week project?
- A 2-week project typically involves one document type (e.g., vendor invoices) and simple validation rules. A 4-week project might involve multiple document types (invoices, receipts, POs), multi-stage approval workflows, and integration with a custom-built ERP. The primary cost driver is the number of unique business rules and integration points we need to build.
- What happens when a new vendor sends a totally different invoice format?
- The Claude 3 model is surprisingly robust to format changes and rarely fails. If it does, the system flags the document and sends it to a human for review. For systemic issues with a major vendor, we can retrain the model with 5-10 new examples. This is a 1-hour task covered by our optional monthly maintenance plan.
- How is this different from using a tool like DocuSign Gen for contract analysis?
- DocuSign Gen is great for templated document generation and analysis within their ecosystem. Syntora builds systems that connect your existing, disparate tools. We handle the messy 'first mile' of getting unstructured data from emails and PDFs into a structured format that can then be passed to your ERP, CRM, or even a system like DocuSign.
- Do we need an engineer on staff to maintain this?
- No. The system runs on serverless infrastructure (AWS Lambda) that requires no server management. The runbook we provide covers common operational tasks. For code changes, any developer with Python experience can take over. We also offer a flat monthly maintenance plan for ongoing support if you have no technical staff.
- What are the ongoing monthly costs after the build?
- Your only ongoing costs are for API usage and cloud hosting. For a typical client processing up to 1,000 documents per month, this is under $30 for the Claude API and under $20 for AWS Lambda. There are no per-seat fees, license costs, or recurring charges from Syntora unless you opt into a maintenance plan.
- Can this system handle handwritten notes on receipts?
- Standard OCR and AI models struggle with handwriting. Our process can extract all typed text reliably, but handwritten amounts or notes will be flagged for manual review. For businesses with a very high volume of handwritten documents, this approach may not be a complete solution, and we would identify that during the initial scoping call.
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