AI gateway architecture for governed enterprise agents
Place model routing, fallback, provider policy, and usage controls alongside governed context and action APIs for enterprise agents.
Read articleBack to all guidance
Guidance library
AI وكيل APIs
نُشرت أدوات وواجهات سياقية مصممة لاستخدام العناصر المتحكمة وأجهزة التأديب.
7 articlesGuidance library
Reviewed enterprise architecture guidance
Narrow the library by controlled topic, audience, pillar, or API product.
Observability for enterprise AI agents and model calls
Trace model requests, retrieval, tool use, business API dependencies, policy outcomes, cost signals, and failures without recording sensitive payloads by default.
Read article
Security architecture for enterprise AI agents
Bound identities, context, tools, operations, outputs, and audit evidence across the path from a user request to enterprise systems.
Read article
Fine-tuning versus RAG for enterprise systems
Choose between behavior adaptation and retrieved evidence by examining knowledge freshness, provenance, evaluation, privacy, and operating responsibility.
Read article
MCP in enterprise AI architecture
Use Model Context Protocol as a connection standard while keeping identity, authorization, business contracts, tool safety, and source operations explicit.
Read article
Multi-model orchestration without hard-coded provider logic
Separate model selection from business context and tool contracts so providers can change without rewriting every agent workflow.
Read article
Production RAG architecture with governed enterprise context
Design retrieval around source authority, chunking, access control, evaluation, provenance, freshness, and failure behavior rather than a vector database alone.
Read article