How the Whole Enterprise AI Platform Fits Together
See how applications, identity, RAG, LLM gateways, models, tools, observability and governance fit into one enterprise AI platform.
Tag: RAG
How Enterprise AI Is Observed and Evaluated
An AI assistant can answer quickly and still be wrong. Learn how traces, retrieval checks, answer evaluation and verified tool outcomes help engineers find the failed step.
How Identity and Authorization Work in Enterprise AI
Authentication identifies the requester; authorization controls what an AI assistant may read or do. See how user context, document permissions, tool policy and target APIs work together.
How RAG Works
RAG retrieves evidence before a language model answers. Follow an incident question through document preparation, permission checks, retrieval and a response that cites its sources.
How Embeddings and Vector Search Work
How can a question about leaving a supplier agreement find a clause called termination for convenience? Follow the path from text to embeddings, vector search and ranked source passages.
How Enterprise AI Systems Work
A language model is only one part of an enterprise AI system. Follow a question from the application through company data, access checks and retrieval to an answer or an approved action.