Domain AI Applications — Overview

Every technique on this site is domain-agnostic by design — a Transformer, a RAG pipeline, an evaluation methodology doesn't know or care whether it's being applied to customer support or cancer diagnosis. This section is the opposite lens: what changes when you apply that general toolkit to a specific domain with its own data, its own risks, and its own regulatory reality.

What's in this section

• Healthcare AI — the flagship domain track: clinical NLP, medical imaging, EHR data, clinical RAG and agents, HIPAA, evaluation, hallucination risk, and human-in-the-loop requirements specific to clinical settings.
• Other Domain Applications — finance, semiconductor, cybersecurity, robotics, and manufacturing, covered at overview depth.

Why Domain Depth Matters

A generic RAG pipeline built with the RAG Engineering techniques elsewhere on this site will run on medical documents without any domain-specific changes — but "runs" and "safe to deploy in a clinical setting" are very different bars. Every domain page in this section is about that gap: what does the general toolkit need on top of it — different evaluation criteria, different regulatory constraints, different human-oversight requirements — before it's actually appropriate for that domain's real stakes.

See the roadmap for the full path.