This is like a hyper-fast, giant interactive map and dashboard that lets insurers watch how thousands or millions of cars are being driven—speeding, hard braking, where and when they drive—so they can price policies more fairly and spot risks in near real time.
Traditional auto insurance pricing relies on coarse factors (age, ZIP code, claim history) and can’t easily ingest or explore massive telematics streams from connected cars. This tool helps insurers turn raw driving data into usable insight for pricing, risk selection, and fraud/risk monitoring, without waiting days for batch reports.
Tight coupling of GPU-accelerated database/analytics engine with location and time-series telematics data, plus domain-specific dashboards and workflows for insurers makes switching costly once embedded into pricing and risk workflows.
Classical-ML (Scikit/XGBoost)
Time-Series DB
High (Custom Models/Infra)
Ingesting and querying very high-volume, high-velocity telematics time-series and geospatial data while keeping query latency low and storage costs manageable.
Early Majority
Rather than just selling a black-box driving score or telematics feed, this focuses on giving insurers an ultra-fast, exploratory analytics environment over raw telematics and geospatial data, enabling in-house data science, custom scoring, and real-time operational dashboards on top of existing usage-based insurance programs.