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A Multi-Agent Chatbot

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CASE STUDY

A Multi-Agent Chatbot

It facilitates efficient handling of user queries involving different data types.

Project Overview

One of our reputed finance client faced the challenge of developing an efficient chatbot solution. To address this, we created Multi-Agent System, an innovative platform that streamlines the chatbot creation process. By simply uploading documents, users can quickly build chatbots that leverage our advanced semantic search capabilities. Multi-Agent System indexes these documents into the Open Search Vector Database, enabling the chatbot to provide accurate and relevant responses to user queries. This cutting-edge technology demonstrates our commitment to delivering innovative solutions that enhance user experience and knowledge retrieval within the financial industry.

Multi Agent Chatbot

The solution leverages a centralized manager agent that coordinates two specialized sub-agents:

The project aimed to create a system that effectively handles user queries involving both structured data (e.g., statistics, calculations) and reasoning-based questions requiring logical analysis or similarity searches.

Agent 1 - Statistical Queries

Handles questions involving data retrieval, calculations, or specific data points.

Agent 2 - Reasoning & Similarity Search

Handles questions requiring reasoning, logic, or similarity search within a large database of documents.

Business Value

Effective Data Handling

Handles both structured data (for reasoning-based questions) and Excel data analysis, combining strengths of statistical insights and context-based answers.
Faster Insights Generation

Answers are delivered quickly, saving time compared to manual analysis.

Reduced Reliance on Data Analysts

Users gain direct access to insights, eliminating the need for analysts to filter data and create reports.
Improved User Experience

User-friendly interface allows users to ask questions and gain insights with ease.