Automate Expense Report Approvals with a Custom AI System

Many small companies start with tools like Expensify for receipt scanning and basic approvals. The OCR technology is convenient, but it cannot understand business context. The system can read an amount from a receipt, but it cannot check if that expense is billable to an active client project or if it exceeds the budget for a specific general ledger code.

Consider a 15-person consulting firm. An employee submits a $150 dinner receipt through an expense app. Your finance person must now manually cross-reference the client name against your project management tool to confirm the project is active. They then check a spreadsheet to see if the client's T&E budget has capacity. This manual checking for a single expense takes 10 minutes and introduces the risk of human error.

More advanced platforms like Ramp or Brex tie spending to corporate cards, which helps enforce vendor-level rules. However, they still fall short on custom logic. They can block a transaction at an unapproved merchant, but they cannot run a multi-step check like: 'Is this employee's department over its monthly software budget by more than 10%?' The approval workflows are linear and cannot query your internal databases for real-time validation.

The structural issue is that off-the-shelf tools operate in a silo. They are not designed to connect to your company's unique sources of truth, whether that is a PostgreSQL database of project codes or a Google Sheet with departmental budgets. This forces your team to perform the most critical validation work outside the platform, negating the value of the tool.

The first step is a discovery process to map your exact expense policy and data flow. Syntora identifies every rule that determines if an expense is approved, such as client billability, project status, or departmental budget. We audit where this validation data lives, whether it is in a CRM, an accounting system, or a custom database.

Based on that map, Syntora would build a custom FastAPI service that acts as your central expense approval engine. For employee reimbursements, Plaid integration connects directly to bank accounts, pulling transaction data without relying on fallible receipt OCR. For policy enforcement, the service queries your specific data sources in real time. For example, it could check a project's status in your Supabase database before approving a related expense. The Claude API can be used to parse unstructured data from receipt notes for additional context.

The delivered system is a production API that plugs into your existing workflow. It can be triggered by a simple web form or an email forwarder. Approved expenses are automatically converted into journal entries and written to your PostgreSQL ledger. You receive the full Python source code, a detailed runbook for maintenance, and the system runs on a cost-effective AWS Lambda architecture that you control.