RAVIN AI, a leader in AI-powered vehicle inspections, today announced a strategic technology partnership with ROLLin’, one of Australia’s fastest-growing digital car insurance brands. The partnership will enable ROLLin’ to digitise post-collision vehicle inspections and assessments. RAVIN’s technology, powered by a global dataset of billions of real vehicle images, uses artificial intelligence to assess vehicle damage from photos taken by end customers or tow truck drivers. The system provides real-time predictions on whether a vehicle is a total loss or repairable, along with automated repair estimates. For ROLLin’ customers, this means faster claims decisions, reduced delays, and a more seamless experience…

In today’s rapidly evolving insurance ecosystem, growth is no longer about simply generating leads or building brand awareness. True growth in the AI era is about precision, adaptability, and orchestration across every stage of the funnel — whether you are a small Insurtech startup, a scaling SMB, or a global enterprise. When I reflect on my philosophy of growth marketing, one guiding principle stands out: data without direction is noise, but data with strategy is power. Startups: Building Momentum from Zero For early-stage Insurtech startups, growth must be about focus and velocity. The temptation is often to market broadly, but…

Click-Ins, a pioneer inAI-powered vehicle inspection solutions, announced today that the United States Patent and Trademark Office (USPTO) has officially granted U.S.Patent No. 12374135B2 for its DamagePrint™ technology – a novel method of creating a unique digital signature of damage from a single image. Unlike generic “damage detection” patents in the market, Click-Ins’ newly granted patent represents deeptechnology rooted in computer vision, visual intelligence, and criminology, built on nearly a decade of rigorous R&D. The DamagePrint™ system goes beyond detecting dents and scratches — it creates a digital fingerprint of each damage, enabling unmatched precision in matching and comparison across…