Think of this as an air-traffic control radar for insurance claims: it constantly scans all open and new claims, flags which ones need attention, and suggests better next steps so handlers and managers can focus on the right work at the right time.
Reduces leakage and cycle time in insurance claims operations by identifying high-risk or complex claims early, prioritizing workloads, and standardizing decision-making, instead of relying on slow, manual review and inconsistent human judgment.
Domain-specific actuarial and claims decisioning IP (pricing/claims models, rules, and workflows) embedded into the platform, plus tight integration with insurer claims systems that makes it sticky once implemented.
Classical-ML (Scikit/XGBoost)
Structured SQL
Medium (Integration logic)
Integration with heterogeneous legacy claims systems and data quality/standardization across lines and geographies.
Early Majority
Positioned as an analytics and decision support layer purpose-built for claims (not a full core-claims suite), allowing it to plug into existing claims systems and augment them with predictive and prescriptive insights rather than requiring complete system replacement.