Automate Expense Reports with Custom AI

Small teams often start with tools like Expensify or a combination of spreadsheets and QuickBooks. Expensify’s SmartScan uses optical character recognition (OCR) to read receipts, but it frequently misinterprets line items or assigns incorrect general ledger codes. This forces someone to manually review every single expense, leaving a 10-person team spending over 5 hours a week just correcting these errors.

Consider a project manager submitting a multi-line hotel folio. An off-the-shelf tool might categorize the entire bill as "Travel," missing that it contains room charges, meals, and parking. Your bookkeeper then has to manually split the transaction in QuickBooks to match your chart of accounts. This process is tedious and error-prone, creating reconciliation headaches at the end of the month.

The problem with platforms like Ramp or Brex is their rigid, one-size-fits-all logic. You cannot implement nuanced approval rules like "If the expense is for Client X and under $200, auto-approve and tag to Project Y." You are forced to adopt their workflow. These platforms are designed for scale and control, not the flexibility a small, dynamic team needs.

The structural issue is that these products are closed systems. Their data models are fixed, and their integration points are limited. You cannot train their categorization models on your company’s specific spending patterns or connect them to internal project management data to automate job costing. You are stuck with their definition of how expense management should work.

The first step is a discovery call to map your exact expense workflow. Syntora reviews your chart of accounts, approval hierarchy, and reimbursement process. We identify the specific rules that off-the-shelf tools cannot handle and provide a scope document detailing the custom logic, data sources, and a fixed-price proposal.

For our own financial operations, we built a system on Express.js and PostgreSQL to automate categorization from Plaid bank feeds, processing syncs in under 3 seconds. For your team, the core would be a FastAPI service using the Claude 3 Sonnet API for intelligent document processing. Employees would email receipts to a dedicated address, where the model extracts vendors, line items, and totals with over 98% accuracy. The backend then applies your custom business logic for approvals and accounting entries.

The delivered system is a lightweight, serverless application deployed on AWS Lambda and connected to a Supabase PostgreSQL database. This stack costs under $50 per month to run for a team of up to 20 people. Your team interacts with a simple interface, and your finance lead gets a dashboard to review approved expenses. You own all the code and data, with no per-user fees.