AI Sales Chatbot Agent

Agent Description:

The AI Sales Chatbot Agentis an intelligent, multi-stage engagement system designed to transform website visitors into qualified sales opportunities. It proactively greets users, utilizes Retrieval-Augmented Generation (RAG) to provide precise product details from internal documentation, and applies a scoring logic to ensure only high-value leads are captured and forwarded to the sales team.

This agent enables organizations to:

  • Scale 24/7 Engagement:Interact with every visitor instantly, regardless of time zone.

  • Automate Lead Qualification:Filter prospects based on budget, intent, and timeline using structured questioning.

  • Ensure Data Accuracy:Deliver technical specs and pricing directly from verified PDF brochures and guides.

  • Streamline Sales Pipeline:Provide the sales team with a pre-analyzed, plain-text summary of high-intent leads.

  • Reduce Friction:Capture contact information naturally within a helpful conversation rather than a static form.

Purpose and Components
  • Purpose: This agent helps to enhance website engagement by delivering real‑time responses to visitor queries, providing instant and accurate product information, and handling technical FAQs autonomously. It filters and qualifies leads 24/7, reducing the burden on sales teams and ensuring that human effort is focused on high‑intent prospects instead of low‑value inquiries.
  • Components:

    • Greeting & Query Analysis Agent: Detects visitors and identifies primary intent.

    • Qualification Agent: Asks discovery questions to assign a Lead Score (Low, Medium, High).

    • Product Info Agent: Uses RAG to answer technical specs from verified brochures.

    • Lead Capture Agent: Finalizes lead records for high-intent prospects.
Supported Capabilities

  • Proactive visitor greeting and identification of returning users.

  • Lead scoring based on budget, purchase timeline, and personal/business use.

  • Accuracy verification by retrieving features and pricing from PDF guides.

  • Automated hand-off of high-value lead summaries to the sales team.

LLM Used

  • OPENAI GPT_4O_MINI

    Note: To learn more about the LLM and to modify its behavior, refer to the Configuring LLM settings section.

Sub-Agents

1. Greeting and Query Analysis Agent

  • Role:Visitor Concierge

  • Scope:Greets visitors and identifies the primary intent of the conversation.

  • Description:Monitors the entry point to detect new users. It delivers a personalized greeting and captures the initial query along with session metadata. It builds the starting "Visitor Context" object and determines if the user is looking for a specific product or general information.

  • LLM Used: Default (Inherits from parent agent).

2. Qualification Agent

  • Role:Lead Scorer

  • Scope:Assesses the potential value and readiness of the prospect.

  • Description: Asks structured questions regarding product interest, budget range, and purchase timeline. It assigns a Lead Score (Low, Medium, High) based on the responses. If answers are ambiguous, it performs follow-up for clarity before updating the global context.

  • LLM Used: Default (Inherits from parent agent).

3. Product Info Agent

  • Role:Technical Product Specialist

  • Scope:Provides detailed information using verified internal documentation.

  • Description:A REACT agent that utilizes an MCP Client to query RAG datasets (e.g., Product_Brochure.pdf). It answers specific inquiries about features, pricing, and FAQs. It translates complex technical data into simple, conversational summaries to aid the visitor's decision-making.

  • LLM Used: Default (Inherits from parent agent).

4. Lead Capture Agent

  • Role:Conversion Manager

  • Scope:Collects contact details and finalizes the lead record.

  • Description:This agent activates only if the lead score is Medium or High. It requests the visitor’s name, email, and phone number. It compiles a final "Lead Record" including the conversation summary and specific product interests for internal sales review.

  • LLM Used: Default (Inherits from parent agent).

Tools Used:

  • MCP Client (RAG): Connects to the knowledge base to extract accurate info from Product_Brochure.pdf and Product_Guide.pdf.

Note: For details on modifying the Tools, refer Tools Library section.
Agent Workflow Behavior Summary

  1. Input: A visitor lands on the page or sends a "Hi" message.

  2. Greeting & Analysis:

    • The bot welcomes the user and logs the entry page.

    • Identifies if the visitor is a new or returning user.

  3. Qualification (Filtering):

    • Asks "What is your budget?" and "When do you need this?"

    • Calculates a lead score to prioritize sales efforts.

  4. Information Delivery (RAG):

    • If the user asks technical questions, the bot queries the PDF database.

    • Provides conversational answers (e.g., "The AlphaPro features an i7 processor...").

  5. Lead Capture (Conditional):

    • Condition: If Lead Score = Low → Provides info but does not push for contact data.

    • Condition: If Lead Score = Medium/High → Asks for Name/Email to schedule a follow-up.

  6. Final Output: A structured Lead Record sent to the CRM or Sales inbox.

Sample Questions:

  • I want to buy BetaPhone X, what are the specs, and can you record me as a lead?