Liablix provides an AI‑driven platform that automates vehicle collision reconstruction, fraud detection, and injury evaluation for insurance claim teams.
Funding
Funding not disclosed
Founders
Product
Problem
Insurance claim teams often rely on manual accident analysis, which is time‑consuming, prone to human error, and can miss subtle inconsistencies in vehicle damage or injury plausibility. This leads to delayed settlements, higher fraud exposure, and less accurate reserve calculations.
Solution
Liablix offers an AI‑driven platform that automates vehicle collision reconstruction, fraud detection, and injury evaluation. Its kinematic modeling engine generates detailed impact dynamics, speed, and fault visualizations within seconds, providing scientific precision for claim decisions. The system applies AI checks across altimetric, energetic, and morphological damage dimensions to flag exaggerated or inconsistent claims. By linking crash physics to biomechanical injury models, Liablix supplies data‑backed assessments of injury plausibility, enabling insurers to make faster, fairer, and more defensible claim resolutions.
Target Audience
Primary customers are insurance carriers and claims professionals who need rapid, accurate accident analysis to assess liability, detect fraud, and evaluate injury claims.
Features
- AI‑powered kinematic modeling that reconstructs vehicle collisions in seconds with speed, impact force, and fault visualizations
- Multi‑dimensional damage consistency analysis (altimetric, energetic, morphological) to detect fraudulent or exaggerated claims
- Biomechanical injury evaluation that correlates crash forces with medical injury data for plausibility checks
- Automated report generation with scientific evidence ready for integration into claim workflows
- Cloud‑based platform accessible via web interface, supporting secure data upload and result export