Automated Hours Validation System for Mission Tracking

Problem

Large enterprise clients in the food industry submitted mission-hour reports as massive Excel files—sometimes thousands of lines long—listing worker names, dates, and logged hours.

The operations team had to manually input and cross-check every record against internal databases and worker confirmations, consuming over 50 hours per week and leaving room for human error.

Approach

Built an automated import and validation system allowing clients to directly upload their hour tracking files through a secure interface.

Implemented a Go and Python backend pipeline that parsed, matched, and verified data against internal mission records, flagging inconsistencies for review.

Integrated an LLM-based reformatter via N8n to automatically correct or normalize column structures, date formats, and field naming before ingestion.

Developed a parallel worker-facing interface so each worker could directly confirm or correct their hours, removing the need for manual ops intervention.

Impact

Reduced weekly manual input time from 50+ hours to under 3 hours, limiting human intervention only to conflict resolution.

Increased validation accuracy and reduced payroll discrepancies through automated reconciliation and cross-check logic.

Freed operations bandwidth to focus on strategic client relationships and scaling mission volume without adding headcount.