A key lesson was to measure what matters. From the outset, we defined clear success metrics—latency reduction, resource efficiency and cost improvement.

Across healthcare, providers are rapidly deploying tools such as ambient clinical documentation, while payers are adopting AI-powered agents for a growing range of operational and administrative use ...

Welcome to the MAIT repository! This pipeline, implemented in Python, is designed to streamline your machine learning workflows using Jupyter Notebooks. It is compatible with both Windows and Linux ...

The platform combines Rust's performance with TypeScript's flexibility, creating a next-generation development environment where AI agents assist in development, testing, and deployment workflows.