Federal ML is not commercial ML with extra paperwork. The data is smaller, the latency requirements are stricter, the acceptable failure modes are narrower, and the model you trained last quarter has to still be defensible three years from now when an IG asks how you made a decision. The posts in this cluster are about getting ML into production on GovCloud or Azure Government and keeping it there.
Start with the GovCloud-vs-Azure comparison if you're still choosing infrastructure, then the MLOps piece for the pipeline, and the RAG post if you're doing document-heavy LLM work.