AI Support Agents Need More Than RAG A lot of AI support agents are built like this: User asks → ...AI Support Agents Need More Than RAG A lot of AI support agents are built like this: User asks → ...
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Tooba Khaliq
• Aug 17
AI Support Agents Need More Than RAG
A lot of AI support agents are built like this:
User asks → retrieve documents → send context to LLM → generate answer.
That works for a demo.
It gets much harder in production.
A reliable AI support agent needs:
→ Good retrieval and chunking → Permission-aware knowledge access → Conversation memory → Source-grounded responses → Fallbacks when information isn't available → Evaluation of retrieval + answer quality → Monitoring for hallucinations and failed queries
The LLM is only one part of the system.
I’ve been working with Python, Django, LangGraph, RAG, PostgreSQL and LLM APIs to build AI agents that are designed around the actual business workflow—not just a chatbot UI.
The interesting part isn't making an AI answer.
It's making sure it answers correctly, consistently, and within the right boundaries.
#AI #RAG #LangGraph #AIAgents #Python #Django #Automation #SaaS
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