Automate Your Accounting Department with Custom AI

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.

Syntora's approach would start by integrating with your document sources, whether that's an email inbox, a shared drive, or an existing API. Using the Claude API, we would design a classification and data extraction pipeline in Python. This model would be trained on a small set of your specific documents, typically 20-30 examples, enabling it to accurately identify key fields like 'Invoice Number' and 'Due Date' regardless of variations in layout. Scans would be processed at a minimum of 300 DPI to ensure accurate character recognition.

The core of the system would be a FastAPI service, orchestrating the entire workflow. After Claude extracts the data into a structured JSON object, this service would validate it against your specific business rules. For example, the system could cross-reference extracted purchase order numbers against your existing inventory database, flagging any mismatches or missing information for review in a designated communication channel, while valid documents proceed automatically. Syntora has experience building document processing pipelines using Claude API for sensitive financial documents, and this pattern of data validation and conditional routing would be applied to your accounting documents.

The FastAPI service would be deployed as a serverless function on AWS Lambda. This architecture is event-driven, meaning it only runs when a document arrives, resulting in very low operational costs. The system would then write the extracted and validated data directly to QuickBooks Online or your ERP via its native API. Syntora would configure structured logging with structlog and establish alerts for any processing failures.

As deliverables, you would receive the complete Python source code in your private GitHub repository, along with a runbook explaining how to update vendor-specific rules or system configurations. Syntora's engagement focuses on delivering a maintainable and auditable system you own.