Design and build of an AI-assisted claims processing platform that replaces a decade-old manual workflow with digital intake, automated data extraction and rule-based routing.
Representative engagement — anonymised and illustrative. It describes the kind of problem we solve and the platform we build, not client-confidential performance data.
A mid-size insurance company was processing claims manually through a legacy system built in the early 2010s. Average claims spent well over a week in manual processing, and the error rates that come with retyping data led to frequent disputes and customer dissatisfaction.
We designed and built a cloud-native claims processing platform with AI-driven automation. The system uses NLP to extract structured data from claim documents, an ML-based classification engine to route claims automatically, and a real-time management dashboard for operations visibility.
Digital claim intake and automated document extraction replace manual data entry
ML-assisted classification routes each claim to the right handling queue automatically
A real-time operations dashboard replaces status-request emails and phone calls
Every claim decision is logged in an audit trail that supports dispute handling and regulatory review
Product strategy, architecture and delivery of a multi-tenant property-management SaaS — taking a founding team from vision to a production platform with secure rent payments.
An ML-based demand forecasting system that replaces spreadsheet-driven inventory planning with data-backed reorder recommendations.
