AI-Powered Compliance & Claims Intelligence on Databricks Lakehouse

Project Solution

INNERLUXES deployed a Databricks Lakehouse solution to consolidate structured and unstructured data — driving real-time analytics, more advanced machine learning, and controlled, audited data sharing at scale. The architecture eliminated data silos, accelerated insights, and provided a platform for future innovation.

The Client

The Client is a US-based construction technology and InsurTech company that provides real-time, property-specific building code and compliance information. It serves contractors, insurers, and claims adjusters, and its platform is critical to speed and accuracy. With insurance fraud a costly, industry-wide problem, the Client needed an AI-driven, real-time solution to consolidate data, stream checks, and fight fraud at national scale.

The Approach

Rapid data analytics

• Integrated building codes, property information, weather records, and permits into one Lakehouse.
• Created analytics pipelines to determine compliance trends, enhance estimating calculators, and calculate weather impacts on roofing projects.

ML to automate insights

• Extracted valuable fields from permits, claims, and contractor reports using NLP.
• Developed a materials recommendation engine, code interpretation, and contractor selection.
• Deployed anomaly-detection models to detect data errors or fraudulent claims — AI-powered fraud detection that cut payouts on fraudulent claims by 20–40%.

Real-time data processing and ingestion

• Applied Delta Live Tables (DLT) for declarative ETL with built-in quality checks.
• Used Auto Loader to continuously ingest updated codes, property records, and weather feeds.
• Enabled auto-scaling and serverless compute to increase performance and optimize costs.

Optimization of insurance claims

• Built ML models to predict severity, detect fraud, and manage it through MLflow.
• Implemented a dynamic rule engine to auto-approve low-risk claims.
• Shared data with insurance partners through Unity Catalog using secure data sharing.

The Impact

• Near-real-time compliance and claims intelligence.
• Reduced manual processing time by 60%.
• Accelerated claims resolution by 40%.
• Cut fraud risk significantly, with fraudulent-claim payouts down 20–40%.
• Enhanced operational efficiency, reduced costs, and increased customer satisfaction through a scalable cloud architecture and focused AI models — enabling quick, precise, fraud-resistant roofing compliance and claims processing.

Technologies and Tools

Databricks Lakehouse Platform, Delta Lake, Delta Live Tables (DLT), Unity Catalog, Auto Loader, MLflow, NLP, anomaly-detection models.