Build an AI System for Agency Time Tracking and Invoicing

Most professional services firms use tools like Harvest or Clockify for time tracking. These platforms are excellent for capturing hours but their native invoicing modules are rigid. They cannot enforce client-specific rules, such as capping senior developer hours at 40 per week or flagging administrative tasks that are incorrectly billed to a project code. The result is that a project manager must manually export data to a CSV file every month.

This manual review process is the core bottleneck for a 15-person agency. A project manager spends 5-8 hours cross-referencing timesheet exports against multiple SOWs in a spreadsheet. They check for vague descriptions, hours logged to the wrong project, and work that exceeds contract limits. After cleaning the data, they manually create each invoice in QuickBooks, a process that introduces risk of data entry errors that can lead to revenue leakage of 3-5%.

The structural problem is that time trackers, project management tools, and accounting software are separate systems. Off-the-shelf tools are designed for simple, standardized workflows and their data models cannot be changed. They lack a logic layer that can sit between the timesheet and the invoice to apply the unique billing rules negotiated in each client's SOW. This forces your most valuable project managers into low-value, repetitive data reconciliation work.

The engagement would start with a discovery workshop to map your complete billing cycle, from timesheet submission to invoice payment. Syntora would audit your time tracking software, review 3-5 sample SOWs to understand your billing rules, and document the exact data flow into QuickBooks. You receive a technical scope document outlining the entire system architecture and logic before any code is written.

The technical approach would be an event-driven system built with Python. A FastAPI service running on AWS Lambda would listen for new timesheet entries via a webhook from your time tracker. The Claude API would then parse the entry's description to categorize the work and flag ambiguities. A rules engine, configured in a Supabase database, checks the hours against client-specific SOW limits. This architecture is efficient, running for under $50 per month, and processes each time entry in less than 2 seconds.

The delivered system fully integrates with your existing tools. At the end of a billing period, it automatically generates draft invoices in QuickBooks. Your project manager receives a single summary report highlighting any flagged entries that require a decision. This transforms their role from hours of manual data entry to minutes of exception management. You receive the full source code, a runbook for maintenance, and complete control over the system.