Case Study Summary:

Kyungbang, a global textile manufacturer, manages one of the most complex challenges in its industry: high-volume fiber testing across suppliers and factories worldwide. Data arrived in scattered formats—PDFs, Excel sheets, raw text—forcing engineers to spend hours reconciling numbers before making decisions.

Edge8 partnered with Kyungbang to build an AI-powered quality platform designed to unify that data, flag anomalies in real time, and allow engineers to query results in natural language. The system is becoming the foundation for faster, more confident decisions on the factory floor—and a launchpad for predictive blending and other future AI enhancements.

The Challenge:

Kyungbang’s quality control was slowed by manual, offline workflows that made fast decisions nearly impossible. Eight team members walked daily to more than 100 testing machines that weren’t connected online. Each day, they collected results on drives, keyed them into spreadsheets, and compiled thick printed books for the Director to review. The process left little room for agility when quality issues arose.

• Supplier and factory data scattered across inconsistent formats (PDF, Excel, text)

• Manual entry of results into spreadsheets, then printed for review

• No direct connectivity from testing machines to decision-makers

• Engineers lacked intuitive tools to quickly query or compare test outcomes

Our Approach:

Edge8 worked with Kyungbang to replace manual collection and reconciliation with a unified AI-powered quality platform. The goal was not only speed, but to give engineers and leaders confidence in the insights driving production choices.

• Built an AI-driven document parsing engine to ingest QC reports from any format

• Developed a system for real-time anomaly detection and automated flagging

• Enabled natural language querying for batch, machine, and location histories

• Integrated the system directly into existing QC workflows across facilities

The Result:

The new platform has already reshaped Kyungbang’s quality operations, cutting waste and speeding up decisions that directly impact production efficiency.

• Reduced manual reconciliation time by over 50%

• Engineers retrieve insights instantly using everyday language instead of spreadsheets

• Faster, more confident production decisions across multiple facilities

• Established a scalable foundation for predictive blending and future AI-driven enhancements