Case studies

Insurance claims automation

Outcome: 22% faster claims cycle and improved fraud detection. Approach: RAG triage, human-in-the-loop, ModelOps. Stack: cloud-native app, vector DB, observability. Measures: cycle time, STP rate, loss ratio.

Improved claims efficiency

Retail personalization

Outcome: +12% conversion and +8% AOV. Approach: feature store, recommendation services, A/B testing. Stack: lakehouse, streaming, microservices. Measures: conversion, AOV, retention.

Personalization signals

Industrial predictive maintenance

Outcome: 22% reduction in unplanned downtime. Approach: edge sensing, degradation features, on‑device inference with secure fleet updates. Measures: downtime hours, MTBF, safety incidents, maintenance backlog.