Use AI to Automate Project Billing and Invoicing

Most professional services firms use a combination of time trackers like Clockify or Harvest and accounting software like QuickBooks. While these tools log hours and send invoices, they do not communicate context. The link between a consultant's cryptic time entry and the specific line item in a Statement of Work (SOW) exists only in the project manager's head.

This creates a painful, manual reconciliation process. Consider a 15-person agency. At the end of each month, an operations manager exports a CSV with hundreds of time entries. They must manually read each description, like "Client sync" or "Ad-hoc analysis," and decide if it maps to a billable SOW item or represents unbilled scope creep. This process can take two full days and is prone to errors that cost real money. Forgetting to bill for three hours of "out-of-scope revisions" at a $150/hour rate is a $450 mistake.

The structural problem is that time trackers are databases, and accounting tools are ledgers. Neither is designed to understand the natural language of contracts or the nuance of project work. They cannot distinguish between an in-scope "bi-weekly status report" and an out-of-scope "additional competitive analysis." This gap forces an expensive human to act as the bridge, performing low-value work that an AI is perfectly suited for.

The first step is an audit of your existing documents and data. Syntora would review a sample of your SOWs, time tracking exports, and final invoices from the past 6 months. This discovery process maps your specific billing rules: what defines scope creep, how you handle pass-through expenses, and which project types have unique terms. The outcome is a clear data model for what the AI needs to classify.

The technical approach uses a FastAPI service to connect your systems. The service pulls data from your time tracker's API (e.g., Harvest) and uses the Claude API to parse the natural language descriptions of each time entry. Based on the rules established in discovery, it classifies each entry as In-Scope, Out-of-Scope, or Internal. We've used this same document processing pattern with Claude to analyze financial reports; the logic directly applies to SOWs and time logs.

The delivered system would be a simple web interface where your operations manager can trigger the process. The tool presents a summary showing total billable hours and a list of flagged entries needing human review (e.g., entries without a project code or descriptions matching out-of-scope keywords). Once approved, the system generates a draft invoice in QuickBooks via its API. This transforms a 16-hour manual task into a 30-minute review.