A support chatbot that hands unresolved questions to a real agent
Ampere Support combines an embeddable AI chat widget with a live agent dashboard. It answers from company knowledge, recognizes when the available information is not enough and moves the same conversation to a human agent.
01 / The problem
What the team needed to fix
A chatbot becomes frustrating when it guesses, repeats itself or ends the conversation after failing to answer. Support teams also lose time when an escalated customer has to explain the same issue again.
The system needed a reliable transition from AI to human support while keeping the conversation, customer details and relevant knowledge available to the agent.
02 / The build
How I approached the system
I built an embeddable Next.js widget and a Node.js backend using Socket.IO for realtime communication. LangChain and Together AI power retrieval from company knowledge before the assistant prepares a response.
When the system cannot answer confidently, it creates an escalation, alerts the team through Discord and opens the same conversation in the agent dashboard. Unanswered questions also feed a knowledge-gap view for future improvement.
03 / Capabilities
What the product does
Embeddable chat widget
The support experience can be added to an existing website without rebuilding the site.
RAG answers
Responses use approved company documents instead of relying only on general model knowledge.
Automatic escalation
Unresolved conversations can move to the support queue based on clear conditions.
Live agent handoff
An agent joins the same chat with the earlier messages and customer context.
Realtime dashboard
Socket.IO keeps conversation and availability states synchronized.
Knowledge-gap queue
Questions the system could not answer become visible for content improvement.
04 / Workflow
How the workflow moves
- 01
Receive the question
The visitor starts a conversation through the embedded widget.
- 02
Retrieve company context
The backend searches the approved knowledge source for relevant information.
- 03
Answer or escalate
The assistant responds when grounded context is available and escalates when it is not.
- 04
Continue with an agent
A human joins the existing conversation with the full history visible.
05 / Product screens
Inside the project
Select a screen to inspect the interface, workflow and operational details more closely.
Ampere Support | RAG Chatbot with Live Human Handoff product view 1
06 / What changed
The practical result
- Customers can move from automated help to a person without starting a second conversation.
- Agents receive the earlier messages and context before they reply.
- Unanswered questions become an actionable list instead of disappearing from the support system.
Common questions
Useful context before a similar build
It retrieves relevant information from approved company sources before generating an answer, which helps keep responses grounded in the business knowledge base.
The backend changes the conversation state, notifies an available agent and keeps the existing chat history attached to the same session.
Yes. An embeddable widget can connect to the support backend without replacing the main website or application.
It answers from retrieved approved sources and uses escalation when the available context is not strong enough for a reliable response.
Yes. The human agent joins the same conversation with the earlier messages and session context already available.
They enter a knowledge-gap queue that helps the support team identify missing or unclear documentation.
Work with me
Need a RAG chatbot developer?
I build support assistants that use your knowledge, expose uncertainty and give human agents a clean path into the conversation.
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