Solera has released what it describes as a “ground-breaking update” to its Artificial Intelligence (AI)-powered, end-to-end automotive claims platform, Qapter.
The release is driven by a new approach to Machine Learning, that delivers 40 per cent faster damage detection (in under two seconds) and a more intuitive and easy-to-use system, for a faster, accurate car repair estimate, according to Solera.
“Our continuous investment into core Machine Learning capabilities is accelerating the pace of evolution of Qapter” said Evan Davies, chief technology officer, Solera. “With the continued innovations our team has developed, we can provide a full, detailed repair cost estimate in less time.”
Announced last June, Qapter is the industry’s only globally available end-to-end solution for full digitalisation of the modern claims workflow. The platform’s integrated approach which brings together data science and extensive Repair Science provides, superior accuracy and performance delivering maximum benefits in digitising the claims process.
The updated Qapter solution now provides the user with real-time image quality feedback. Dark, blurred, or over exposed images will be highlighted so better images may be taken. This intuitive user-friendly experience combined with the powerful Machine Learning in Qapter’s AI means that fewer images are required to deliver a better, faster estimate.
The solution also brings higher accuracy for parts and damage detection, with an improved damage localiser. The AI can identify and itemise damages of the same type in the same area, for example, multiple scratches on a front bumper. It can also better detect damage when reflections are present, which can disguise damage and compromise the estimate.
The innovations in this update are available now to Qapter users, delivered directly in the workflow to allow all customers to benefit in a seamless way.