Move beyond the prompt. Learn how to architect robust, scalable, and safe AI applications using Routers, RAG, and Agents.
A production AI system is more than just a model API call. It requires a supporting cast of infrastructure.
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Dynamically directs user requests to the best model.
Simple query? Use a fast 7B model.
Complex logic? Route to GPT-4.
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Intercepts inputs and outputs.
Prevents PII leakage, blocks jailbreak attempts, and filters toxic content before it reaches the user.
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Stores domain knowledge as embeddings.
Allows the LLM to access millions of documents via RAG (Retrieval Augmented Generation).
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Frameworks like LangChain or LangGraph that manage the flow.
They handle tool execution, retries, and maintaining conversation history.
Click the components to trace how data flows through a modern Enterprise GenAI architecture.
Click any node in the diagram to understand its role in the system architecture.
The interface (React, Streamlit, Mobile) where users interact. It maintains the session state but contains no business logic.
Handles Rate Limiting, Authentication, and Logging. Essential for cost control to prevent abuse of expensive LLM tokens.
Input: Detects Prompt Injection ("Ignore previous instructions") or PII.
Output: Validates JSON schema and checks for hallucinations or toxicity.
The control center (often built with LangChain). It decides: "Do I need to search the database? Do I need a calculator? Or can I answer directly?"
Retrieves relevant context from a Vector Database (Pinecone/Weaviate) to ground the model's answer in facts.
The models themselves. Often a mix of hosted (GPT-4) and open-source (Llama 3 via Groq) depending on the complexity routed by the orchestrator.
External capabilities: Web Search, SQL Database connectors, or Python code interpreters that the agent can "call".
Best for: Question Answering over private data.
Test your system design knowledge.
1. What is the primary purpose of a "Router" in GenAI architecture?
2. Where should "Guardrails" be placed in the stack?
3. Which component acts as the "Long-Term Memory" for the system?