AI-Based Business Document Analysing Chatbot

GB's of Document Summarizer (RAG)+ AI Chatbot for Sales
Project Overview
We are looking for an experienced AI/ML + Full-Stack Developer to develop a software platform that can upload, analyze, summarize, and intelligently interact with business documents, along with an AI-powered chatbot designed specifically for sales and customer engagement.
The system should use modern AI/LLM technologies to extract meaningful information from documents and provide accurate, context-aware responses through a conversational interface.
Core Requirements
1. Document Summarization System
Upload documents such as PDF, DOCX, TXT, and other commonly used formats.
Extract and process text from uploaded documents.
Generate AI-powered summaries.
Support both short summaries and detailed summaries.
Allow users to ask questions about the uploaded document.
Provide answers based strictly on the document's content.
Highlight or reference relevant sections/pages where possible.
Handle large documents efficiently using chunking/RAG techniques.
Maintain document history and previously generated summaries.
2. AI Chatbot for Sales
Develop an AI chatbot that can be used by businesses to engage website visitors and generate/qualify sales leads.
The chatbot should be able to:
Answer customer questions using a predefined knowledge base.
Understand natural-language conversations.
Provide information about products/services.
Recommend relevant products/services based on customer requirements.
Ask qualification questions.
Capture lead information such as name, email, phone, requirements, etc.
Identify customer intent and buying signals.
Maintain conversation context.
Escalate the conversation to a human sales representative when required.
Store conversation history and lead information.
Provide an admin interface to review conversations and leads.
3. AI / Knowledge Base
The platform should allow administrators to provide information that the AI can use, such as:
Product/service documentation
FAQs
Company information
Pricing information
Sales material
Uploaded documents
Website content
The chatbot should use RAG/vector search or an equivalent approach so responses are based on the company's actual data rather than relying only on the LLM's general knowledge.
4. Admin Dashboard
An admin panel should provide:
User management
Document management
Summary management
Knowledge-base management
Chatbot configuration
Conversation history
Lead management
Basic analytics
AI/API usage monitoring
Prompt/configuration management
Technical Expectations
The developer should have experience with:
LLM / Generative AI
OpenAI or equivalent LLM APIs
RAG (Retrieval-Augmented Generation)
Vector databases
Document processing
Embeddings
Prompt engineering
AI chatbot development
REST APIs
Modern frontend and backend frameworks
Secure authentication and authorization
Cloud deployment
The technology stack can be proposed by the developer based on the project requirements, but the architecture should be scalable, secure, maintainable, and production-ready.
Important Requirements
AI responses should be accurate and grounded in the provided documents/knowledge base.
The system should minimize hallucinations.
API keys and customer data must be securely handled.
The application should be designed for future scalability.
Clean, well-documented, and maintainable code is required.
The solution should be deployed to a production server and properly tested.
Deliverables
Complete source code
Document upload and AI summarization module
Document Q&A functionality
AI sales chatbot
RAG/knowledge-base system
Lead capture and management
Admin dashboard
Database and API implementation
Production deployment
Technical documentation
Basic testing and bug fixing
Developer Requirements
Please apply only if you have demonstrable experience building AI/LLM applications, document-processing systems, RAG systems, or AI chatbots.
When applying, please share:
Examples of similar AI projects you have developed
Your proposed technology stack
Which LLM/API you recommend and why
Your approach for handling large documents
Your approach for RAG/vector search
Estimated development timeline
Estimated project cost
We are looking for a developer/team who can build this as a production-ready AI SaaS/application, not just a basic ChatGPT API integration.