ARVK Labs · Learn · Gen AI Explained

Anatomy of a production AI system

A demo answers in a notebook. A production system runs a full stack — from raw data to a deployed, guarded, monitored answer. Watch a request flow all the way down.

Data SourcesDocuments · Databases · SharePoint · APIs Ingestion & Vector IndexChunking · Embeddings · Vector DBPHASE 2 Retrieval — RAGHybrid search · Re-ranking · CitationsPHASE 2 Reasoning & AgentsLLMs · LangGraph · Tools · MemoryPHASE 1 · 3 Guardrails & EvaluationRAGAS · Safety · Prompt-injection defencePHASE 4 Serve · Deploy · ObserveFastAPI · Azure Container Apps · CI/CD · LangfusePHASE 5 DeliveryWeb · Microsoft Teams · API → end users
Ground itReal data is indexed and retrieved (RAG).
Reason & guardLLMs/agents act; guardrails & eval keep it safe and measured.
Ship & watchDeployed with CI/CD, traced and cost-monitored.
The gap between a hobby project and a production AI engineer is everything below the LLM box — retrieval, guardrails, deployment and observability. FORGE is built around shipping this entire stack, four times over.
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