GoldenTech was able to assist one of our customer’s in the area of machine learning by saving them personnel and logistics for maintenance of its fleet assets that included light duty trucks. We were able to deploy a predictive analytics solution to come up with a unique solution for determining ‘repair v/s replace’ options for a fleet of over 10,000 light duty trucks. Our team leveraged on-board telematics from fleet assets to a cloud-based SAP analytics engine to deliver predictive model for fleet technicians. The solution provided out client with a targeted list of assets that needed to be replaced based on the preventative maintenance history coming out of the asset management tool. Our client was able to deliver cost savings attributable to decreased manual processing of information.
Problem Statement: Our client had 2 different work management systems that were used within the Supply Chain organization, and used similar, yet disparate lifecycle management approaches when it came to contracts, SoWs, MSAs etc. The customer did not have visibility into contract spend, vendor overlap between systems, and most importantly it lacked the tactical ability to check rebate clauses on contracts across the enterprise.
Our Approach: GoldenTech offers our technical capabilities and deep understanding to in ML domain via our past performance referencing Machine Learning platforms that deliver enterprise-wide costs savings in future acquisition planning by parsing out rebate and bulk discount clauses in contract documents. Our solution was able to parse documents via S3 buckets running in a containerized infrastructure via Kofax and ML. We were successful in the provision of overall architectural oversight and analysis design to deliver this high-performance solution.