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.
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Guidance library
AI Agent APIs
Publish bounded tools and context interfaces designed for governed agent and copilot use.
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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.
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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.
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Fine-tuning versus RAG for enterprise systems
Choose between behavior adaptation and retrieved evidence by examining knowledge freshness, provenance, evaluation, privacy, and operating responsibility.
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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.
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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.
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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.
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