AI Process Automation

Background

A leading electronics manufacturing company depended heavily on manual reporting, spreadsheet-based updates, and repetitive workflows. With over 40 daily operational tasks being performed manually, production teams were losing crucial hours each day performing non-value-added work. Leadership lacked real-time insights due to delayed reporting cycles and fragmented systems.

Business Challenge

The company struggled with operational delays, inconsistent reporting, and a lack of real-time visibility into production metrics. Over 100 hours per week were spent on manual data entry, Excel updates, shift logs, quality checks, and document routing. These inefficiencies caused production slowdowns, approval delays, and communication gaps across departments.

Discovery & Analysis

BrevaNext spent two weeks analyzing the workflows, mapping process bottlenecks, and studying the ERP system constraints. We identified 27 high-impact automation opportunities across production, quality control, and inventory management. A unified workflow automation blueprint was created to streamline operations end-to-end.

Solution Architecture

      • AI Workflow Brain – Automated approvals, triggered alerts, validated inputs  
      • RPA Bots (UiPath + Power Automate) – Automated reporting, shift logs, QC summaries  
      • Automated Reporting Engine – Python-based ETL + real-time dashboard refresh  
      • Smart Document Automation – AI-powered invoice & QC extraction  
      • Integration Layer – ERP + Excel + SharePoint connected into seamless workflow  
    

Implementation Approach

      • Phase 1 – Pilot automation for reporting & shift updates (72% reduction in workload)  
      • Phase 2 – Full RPA rollout for QC, production logs, and reconciliation  
      • Phase 3 – Implemented automated reporting dashboards  
      • Phase 4 – Introduced real-time monitoring & optimization mechanisms  
    

Business Impact