A reference architecture for a secure, RAG-based enterprise AI assistant built from open-source models, with policy guardrails for redaction and access control.

A curated map of open-source MCP tools — frameworks, CLIs, and automation platforms — for building agentic AI workflows from proven components.

The eight-principle foundation for building and using AI responsibly — safety, privacy, fairness, transparency, human oversight, security, IP, and operational excellence — and how each applies across the AI lifecycle and to autonomous agents.

How AI turns rule-based automation into intelligent automation — systems that handle unstructured data and variable workflows, not just scripted, repetitive tasks.

Introduces NLP, the AI discipline that lets machines read, interpret, and generate human language. Covers the processing pipeline, the NLU/NLG split, common applications, the arc from rules to transformers, and NLP’s role as the intent engine for agentic AI.