June 4th, 2026

ChargePulse was inspired by a costly problem on an engineering project: labor hours were charged to the wrong billing code, but the error was not discovered until the project had already closed. As a result, the company absorbed thousands of dollars in costs that should have been billed to the customer.

To prevent similar issues, I developed ChargePulse, a project-management and financial-monitoring tool that compares the company’s internal labor transactions with the original project estimate. Through a centralized dashboard, project managers can see how many hours have been charged against each work category, monitor current burn rates, and identify areas trending toward an overrun. Categories approaching their allotted hours are automatically highlighted, allowing managers to investigate unexpected charges or adjust project resources before the budget is exceeded.

ChargePulse also distributes weekly email summaries showing recently charged hours and changes in project status. These updates give managers an opportunity to catch incorrect billing codes and other discrepancies early, rather than discovering them during project closeout.

The project’s primary technical challenge was data collection. Transaction records were stored in IFS, but direct API access was limited to IT-managed systems. To work within this constraint, I developed an automated extraction process that securely retrieved the necessary records using my authorized account. A Python-based data pipeline then cleaned and consolidated the transaction data, mapped each charge to the appropriate estimate category, and calculated metrics such as hours used, hours remaining, utilization percentage, and projected burn rate.

The processed results were delivered through a secure web application with individual login credentials. Managers could select their projects and view daily updates to labor usage, estimate performance, and potential overruns.

By turning fragmented transaction records into timely, actionable information, ChargePulse helps project managers protect margins, improve billing accuracy, and intervene before small discrepancies become costly problems.