24/7 Customer Service with an AI Agent
An agent that searches your documentation with RAG, resolves complex queries and hands over to a person when needed.
An autonomous AI agent that acts as your first line of support. It searches your internal documentation with RAG (Retrieval-Augmented Generation), answers queries in context, and hands over to a person when it detects that manual intervention is needed.
The problem
Your support team spends hours answering the same repetitive questions by digging through documentation, FAQs and past tickets. That is time they could spend on complex cases that really need human expertise.
How the agent works
Built on LangGraph, with contextual decisions
The customer sends a query
The agent receives the query by chat, email or webhook and works out what the user wants.
It searches the documentation with RAG
It queries your vector database with semantic embeddings to find the relevant information in FAQs, internal docs and past tickets.
It reasons and writes the answer
The agent uses LangGraph to decide: do I have enough information? Is the answer clear? Or do I need a person?
It hands over to a person when needed
If it detects ambiguity, an out-of-scope case or a decision that needs a person, it opens a ticket with the full context for your team.
Tech stack
Expected results
- Response time under 10 seconds
- 60-70% of queries resolved without a person
- 24/7 availability at no extra cost
- 40-50% less load on support
Is your case similar?
Let's talk. I'll tell you honestly whether an AI agent fits your process.
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