AI Damage Valuation
The RAALS AI Damage Valuation module revolutionizes the way insurers assess vehicle damage by combining computer vision, machine learning, and real market data into a single, automated process.
Designed for speed and precision, it analyzes photos or videos of damaged vehicles, detects affected parts, classifies severity, and estimates repair or replacement costs in real time.
The system seamlessly integrates with existing insurance workflows and databases such as Eurotax, providing instant, data-driven repair cost estimates and generating comprehensive reports — complete with damage maps, part lists, and repair time breakdowns.
It also automatically validates VIN and license plates, detects image manipulation, and compares submissions against historical records to flag potential fraud or exaggeration.
By automating repetitive and error-prone tasks, the module empowers insurance companies to achieve up to 10× faster claim processing, 70% cost reduction, and a significant boost in customer satisfaction.
With AI-driven accuracy, full transparency, and real-time fraud safeguards, RAALS AI Damage Valuation transforms claims assessment into a faster, smarter, and more trusted process.
Automated image analysis: Detects, classifies, and describes damage areas using advanced computer vision.
Real-time cost estimation: Generates repair and replacement cost estimates instantly using live market and parts data.
Fraud detection: Identifies manipulated, reused, or inconsistent images; flags suspicious patterns automatically.
VIN and plate recognition: Verifies vehicle identity through integrated AI-powered recognition.
Comprehensive reporting: Creates structured, exportable reports (PDF/Word) with damage summaries, repair time, and cost details.
Seamless workflow integration: Connects effortlessly with RAALS Case Management, RIF Image Forensics, and insurer systems via API.
Efficiency & ROI: Boosts assessor productivity, reduces manual errors, and delivers measurable savings across the claims process.
Transparency & trust: Ensures consistent, explainable results that strengthen confidence between insurers and customers.