How to build a Customer Support Chatbot

This agent streamlines customer support by searching internal knowledge bases, generating concise answers, and automatically recording Q&A pairs in Airtable.

Challenge

Financial advisors and private bankers struggle to quickly access and synthesize up-to-date client information and relevant product details from multiple internal systems before client meetings.

Industry

Finance

Department

Customer Success

Integrations

SharePoint

Airtable

Workflow Overview

1. Customer Question (Input Node)

  • Purpose:
    This is where the user (customer or support rep) enters their question or issue.

  • Node: in-0 (Customer Question)

2. Knowledge Search (Parallel Retrieval)

  • Purpose:
    The workflow searches for relevant information to answer the question using two sources:

    • A. Search Knowledge Bases (Action Node):
      Uses the "Search Knowledge Bases" action to query a specific knowledge base (configured in the node) with the customer’s question.

    • B. SharePoint 2 (Knowledge Base Node):
      Searches a SharePoint knowledge base for relevant content.

  • Nodes:

    • action-0 (Search Knowledge Bases)

    • knowledgebase-2 (SharePoint 2)

  • How it works:
    Both nodes receive the customer’s question as input and independently search their respective sources.

3. AI-Powered Answer Generation

  • Purpose:
    An AI model (OpenAI LLM) combines the original question and the retrieved knowledge base results to generate a helpful, concise answer.

  • Node: llm-1 (OpenAI)

  • How it works:

    • The LLM receives:

      • The customer’s question

      • Results from both knowledge search nodes

    • It generates a brief answer, asks for clarification if needed, and proposes follow-up questions.

    • The LLM also provides citations for the sources it used.

4. Answer Output

  • Purpose:
    The generated answer is displayed to the user.

  • Node: out-0 (Answer)

  • How it works:
    The output from the LLM is sent directly to this node for user viewing.

5. Airtable Instruction Generation

  • Purpose:
    The workflow prepares a natural language instruction for Airtable, summarizing the question and answer for record-keeping or follow-up.

  • Node: llm-2 (OpenAI 2)

  • How it works:

    • Receives:

      • The original question

      • The answer generated by the first LLM

    • Converts these into a clear instruction for Airtable, following a specific format.

6. Write to Airtable

  • Purpose:
    The workflow writes the instruction (from the previous step) into a specified Airtable base and table.

  • Node: action-1 (Write to Airtable)

  • How it works:

    • Takes the formatted instruction from the second LLM

    • Uses the Airtable connection and table details to create a new record

Node-by-Node Summary

Type

Purpose/Description

Input

User enters a customer question

Action (Knowledge)

Searches a configured knowledge base for relevant info

Knowledge Base

Searches SharePoint for relevant info

LLM (OpenAI)

Generates a concise, helpful answer using all retrieved info

Output

Displays the answer to the user

LLM (OpenAI 2)

Converts the Q&A into a natural language instruction for Airtable

Action (Airtable)

Writes the instruction into a specified Airtable base/table

How the Flow Helps

  • Automates customer support:
    Answers questions using both internal and SharePoint knowledge.

  • Records interactions:
    Summarizes and logs each Q&A in Airtable for tracking, analytics, or follow-up.

  • Ensures traceability:
    Citations are included for transparency and compliance.

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Let’s Build AI Agents, Together

Book a demo to see how AI agents can help your team process unstructured documents and perform complex analysis faster and more accurately.

Get started

Let’s Build AI Agents, Together

Book a demo to see how AI agents can help your team process unstructured documents and perform complex analysis faster and more accurately.