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PROJECT SHOWCASE

Case Study
Repair House Management System

AI-enhanced repair management integrating PCB component detection, automated billing, and end-to-end lifecycle tracking — built for Sanstar Microsystems, India.

Repair House App UI

The Client

Sanstar Microsystems

Sanstar Microsystems is a premier Make in India manufacturer specialising in high-reliability power electronics — SMPS units and industrial battery chargers for global industrial sectors. Their technical service team handles complex hardware repair workflows requiring precision tracking, accurate billing, and full accountability across every repair job.

The Challenge

Operational Inefficiency

Manual component identification and paper-based tracking led to frequent billing errors, inconsistent warranty validation, and no real-time visibility into repair timelines. This fragmented process resulted in slower turnaround times and difficulty maintaining accurate profit margins across complex hardware service jobs.

Our Solution

Engineering the Future

Technologies Powering This Project

PYTHON FLET SQLITE API MATERIAL 3 FIGMA PYTHON FLET SQLITE API
Faster Diagnosis

600%

AI identifies PCB faults in seconds, not hours.

Data Loss

Zero

Every repair stage logged — no gaps, no disputes.

Team Adoption

98%

Technicians switched from paper logs in one day.

Impact Delivered

AI-powered component detection replaced slow manual inspection, automated billing eliminated calculation errors, and end-to-end job tracking gave management real-time visibility into profit margins and technician output.

"This platform has seamlessly harmonized our technical workflows — blending precision component detection with automated tracking to deliver a faster, more transparent, and highly profitable service experience."
— Sanstar Microsystems, Operations Head

Work with Viprush

Elevating enterprise standards through human-centric engineering.

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