Describe your GenAI stack and the AI draws it end to end — providers, retrieval, orchestration, safety layers, and the applications on top
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Design full-stack LLM applications with routing, retrieval, tooling, and safety layers
Map ingestion, embeddings, vector stores, and LLM orchestration for grounded generation
Describe your agent and the AI draws the loop — model, tools, memory, guardrails, and the humans and systems it touches
Common questions about ai generative ai architecture generator
The model providers and the gateway in front of them, retrieval and its sources, prompt and version management, safety layers (moderation, PII filtering, evals), observability with cost tracking, and the applications consuming it all. The generator treats the gateway and safety layers as first-class, because that is where enterprise reviews focus.
Yes — generate both and the differences are immediately visible: where data leaves the boundary, what you operate, and where the cost sits. That side-by-side is the standard artifact for the build-vs-buy meeting.
OpenAI, Anthropic, Azure OpenAI, Bedrock, and Vertex on the provider side; vLLM and Ollama for self-hosting; pgvector, Pinecone, and Weaviate for retrieval; Langfuse and LangSmith for observability — named in your prompt, drawn with the right icons.
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