Technical tutorials on
building industrial AI

Sensor data ingestion, per-asset Isolation Forest anomaly detection, health scoring, and an LLM advisor that explains failures in plain English. Full walkthrough with real code.

Why standard RAG breaks on technical manuals — and what to do instead. Chunking strategies, hybrid search with pgvector, self-hosted embeddings, citation-aware retrieval, and BYOM architecture.

Why Model Context Protocol is the missing layer between AI agents and enterprise systems. Building adapters for ERPs, SCADA historians, and legacy databases — with human-in-loop as a first-class pattern.

Why SMB manufacturers can't just call the OpenAI API. Data sovereignty on the shop floor, hybrid inference routing, a fully local Docker Compose AI stack, and practical hardware recommendations.

How to build AI agent infrastructure where users never see each other's data — pluggable adapters, Redis session caching, PostgreSQL persistence, and role-based tool access in FastAPI.