Overview

In North America and around the world, VIN is widely used as a primary information key in government vehicle registers, police information systems, auto insurance companies, auto leasing companies, auto repair shops, roadside assistance companies, etc. VIN data quality is essential not only for government administrative and security reasons but also very important in commercial applications. Most VIN errors occur in manual processes during transcribing or copying VINs from documents to information systems.

Our VINfix API 2.0 provides a powerful and reliable technology designed to help your clients correct typographical errors in problem VINs. Behind the scene, two state-of-the-art machine learning algorithms do the wonders. Utilizing unsupervised learning, they are trained on our huge in-house VIN database to find clusters of hidden grouping/patterns. These clusters are modeled by measuring similarity which is defined by various distance metrics.

Equipped with our VINfix technology, your clients will never have to scratch their heads when a VIN is tagged as "invalid" by VIN decoders and they most likely have no idea what's wrong with the VIN, let alone how to correct it. Our VINfix technology can figure that out for them in a split second.