AI-Driven Hospital Invoice Verification

The client wanted to automate and improve the accuracy of its hospital-invoice verification process using machine learning. The existing approach relied on manual workflows that were inefficient, error-prone, and difficult to scale with growing case volumes.

Templefield Technologies was engaged to design and implement a scalable, Python-based ML microservice application that streamlines invoice verification, integrates cleanly with existing systems, and adheres to modern DevOps practices.

• Developed a Python microservice leveraging PyTorch for machine learning and FastAPI for the application interfaces
• Implemented PostgreSQL and Amazon S3 as the data infrastructure
• Applied Docker containerization and Kubernetes orchestration with Helm for deployment management
• Deployed Kafka for event-driven streaming between services
• Established data governance frameworks to safeguard quality and compliance

The solution improved invoice-verification accuracy and efficiency, reduced manual effort, and provided the client with a scalable, automated system ready for future enhancements. By guiding manual processing, it reduced the cost per invoice by 16%.