Enterprise LLMs differ from consumer AI in that they must integrate with private company data, comply with security and regulatory requirements, and connect to internal systems. Key architectural decisions include using RAG to ground model outputs in proprietary knowledge, choosing between cloud APIs, self-hosted open-weight
Table of contents
How RAG connects LLMs to your organization’s knowledgeDeployment models for enterprise LLM infrastructureSecurity controls and guardrails in productionMonitoring LLM behavior and controlling costsEvaluating your enterprise LLM architectureShip Faster with AIFAQs on enterprise LLM implementationSort: