AutoStream Social-to-Lead Agentic Workflow

A Social-to-Lead Agentic Workflow for AutoStream SaaS using LangGraph and RAG

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This project implements a production-style AI Sales & Support Agent for AutoStream, built using LangGraph, LangChain, Gemini (Google Generative AI), and Retrieval-Augmented Generation (RAG).

AI-powered conversational agent for AutoStream - Social-to-Lead workflow with LangGraph

Conversational AI Agent for AutoStream using RAG, intent detection, and lead capture workflow.

GenAI sales agent for AutoStream SaaS using LangGraph, RAG, and stateful lead capture workflow.

AutoStream LangGraph Agent is a production-style conversational AI agent built using LangGraph and LangChain, designed to simulate a real SaaS assistant workflow.

In this project, I built a GenAI-powered conversational agent -AutoStream that follows an agentic workflow to identify user intent, retrieve verified product information via RAG and conditionally capture leads using controlled tool execution.

"AutoStream Social-to-Lead Agent automates lead capture from social media platforms, processes user interactions, and converts them into actionable sales leads. It streamlines marketing workflows, improves lead response time, and enhances overall customer engagement efficiency."

AutoStream AI Agent is a Flask-based AI application using Retrieval-Augmented Generation (RAG) to provide real-time, document-based answers on product pricing, features, analytics, and workflows through an interactive chat interface, wrapped in a Netflix-inspired UI.