Automate Expense Report Auditing and Approval Workflows

Many SMBs start with tools like Expensify. Its OCR is a good first step, but it often misreads line items, forcing manual corrections. More importantly, its policy engine is built on rigid, if-then rules. The system cannot handle nuanced logic, like a multi-level approval where a project manager can approve up to $500 for their direct reports, but anything over that amount requires a director's sign-off.

Newer platforms like Ramp or Brex are excellent for corporate card management, but their expense software often struggles with out-of-pocket reimbursements or complex multi-line reports. Consider a 30-person consulting firm. An employee submits a single report containing a software subscription, a client dinner, and a flight. Each of these items has a different policy and requires a different approval path. Existing tools cannot split a single report for parallel approvals, creating a bottleneck in the finance department.

This forces the accounting team to become the human integration layer. They manually check each line item against a policy document, cross-reference project codes in QuickBooks, and chase employees for missing receipts. For a team with 15 active projects, this can mean 5-10 hours per month spent on low-value, error-prone auditing work that employees and accountants both dislike.

The structural problem is that off-the-shelf tools have a fixed data model designed for the most common use cases. They cannot connect to your project management system to verify a charge against a budget or query your HRIS to confirm an employee's approval limit. They operate in a silo, which means the most important business context remains outside the system.

The first step is a process audit. Syntora would map your exact approval workflows, document every policy rule, and analyze 3-6 months of past expense reports to identify the most common rejection reasons. This discovery phase ensures the system is built around your real-world operations, not a generic template. You receive a technical specification detailing the logic before any code is written.

The core of the system would be a FastAPI service hosted on AWS Lambda that listens for new expense reports, typically submitted via email or a simple web form. The service uses an OCR library to extract data from receipt images or PDFs. That structured text is then sent to the Claude API, along with your specific policy rules, to perform the audit. The AI checks amounts, dates, vendors, and expense categories, returning a clear pass, fail, or flag-for-review decision with a one-sentence explanation.

The delivered system integrates directly with your existing software. For example, it would post approved expenses as journal entries in QuickBooks and log every audit decision in a Supabase database for a permanent, searchable record. A flagged report would trigger a Slack notification to the appropriate manager with the AI's summary and a link to approve or deny. A 20-item report is typically processed in under 60 seconds from submission to final notification.