You will get AI RAG Chatbot: Custom Knowledge Base Q&A System
Project details
I build AI chatbots that answer questions using YOUR documents - no hallucinations, just accurate answers grounded in your data.
WHAT YOU GET:
• RAG-Powered Chatbot - Your chatbot retrieves relevant information from your documents before generating responses. This means accurate, context-aware answers every time.
• GPT-4o / Claude Integration - Uses the latest AI models for natural, helpful responses that understand context and nuance.
• Vector Database Setup - Your documents are indexed with semantic embeddings for fast, relevant retrieval. Works with PDFs, TXT, Markdown, DOCX, or web content.
• Production-Ready API- Clean REST API endpoint you can integrate into your website, app, or internal tools.
• Demo Interface Included - Test your chatbot immediately with a working demo UI.
PERFECT FOR:
• Customer support automation
• Internal knowledge bases
• Product documentation Q&A
• FAQ chatbots
• Training material assistants
• Legal/compliance document search
I have built production RAG systems handling 1000+ daily queries with 95%+ accuracy. Clean code, full documentation, and deployment support included.
Ready to turn your documents into an intelligent assistant?
WHAT YOU GET:
• RAG-Powered Chatbot - Your chatbot retrieves relevant information from your documents before generating responses. This means accurate, context-aware answers every time.
• GPT-4o / Claude Integration - Uses the latest AI models for natural, helpful responses that understand context and nuance.
• Vector Database Setup - Your documents are indexed with semantic embeddings for fast, relevant retrieval. Works with PDFs, TXT, Markdown, DOCX, or web content.
• Production-Ready API- Clean REST API endpoint you can integrate into your website, app, or internal tools.
• Demo Interface Included - Test your chatbot immediately with a working demo UI.
PERFECT FOR:
• Customer support automation
• Internal knowledge bases
• Product documentation Q&A
• FAQ chatbots
• Training material assistants
• Legal/compliance document search
I have built production RAG systems handling 1000+ daily queries with 95%+ accuracy. Clean code, full documentation, and deployment support included.
Ready to turn your documents into an intelligent assistant?
AI Development Type
Deep Learning, Knowledge Representation, Model Tuning, Recommendation System, Software MaintenanceAI Tools
OpenCV, PyTorch, TensorFlowAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$800
|
Standard
$1,500
|
Advanced
$2,500
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 21 days |
Number of Revisions | 2 | 3 | 5 |
AI Model Integration | |||
Detailed Code Comments | - | ||
Knowledge Graph | - | - | |
Model Documentation | - | ||
Ontology | - | - | |
Source Code | |||
Taxonomy | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$200
Additional Revision
+$100
Additional 500 Documents
(+ 3 Days)
+$300
Custom Chat UI Design
(+ 5 Days)
+$400
Deployment to AWS/GCP
(+ 2 Days)
+$250Frequently asked questions
About Gaurav
AI/ML Engineer & Full Stack Developer | RAG | GPT Integration | Mobile
Noida, India - 9:18 pm local time
What I bring to your project:
Full Stack Development -> End-to-end product development with React Native (Expo), React, NodeJS/Express, FastAPI, and MongoDB. I architect scalable systems that handle real users and real traffic.
AI Engineering & LLM Integration -> Hands-on experience building production AI pipelines with GPT-5, computer vision, OCR, and multimodal processing. I design prompt systems that deliver consistent, high-quality results.
RAG (Retrieval Augmented Generation) -> Custom RAG implementations for domain-specific AI assistants, including vector stores, semantic search, and context-aware response generation.
Mobile App Development -> Native-quality cross-platform apps using React Native & Expo SDK 54, with in-app purchases (iOS & Android), deep linking, and offline-first architecture.
Cloud & DevOps -> AWS (Elastic Beanstalk, S3, ElastiCache), Docker, Redis, real-time streaming (SSE), and production monitoring with Sentry.
Recent project highlights:
- Built an AI-powered video analysis platform processing thousands of videos monthly with GPT vision models
- Developed a real-time product extraction pipeline with parallel detection, deduplication, and affiliate integration
- Created a multi-region mobile app with subscription billing, device-based auth, and quota management
- Implemented production RAG systems for AI assistants with custom knowledge bases
- I write clean, maintainable code with proper error handling, security best practices, and comprehensive documentation. Let's build something great together.
Completed Projects -
1. AI-Powered Video Analysis Platform - Built a full-stack mobile application that uses GPT vision models to analyze video content in real-time. The system processes videos from multiple social platforms, extracts meaningful data using computer vision and OCR, deduplicates results using AI, and presents actionable insights to users.
Tech -> React Native, Expo, FastAPI, Python, GPT-4/5, OpenAI Vision API, MongoDB, Redis, AWS
2. Production RAG System for AI Assistant - Designed and implemented a Retrieval Augmented Generation system that powers an intelligent assistant. Features include custom knowledge base management, semantic search, context-aware responses, and streaming output for real-time interaction.
Tech -> Python, FastAPI, OpenAI API, Vector Embeddings, Redis, SSE Streaming
3. Multi-Region Subscription Mobile App - Developed a cross-platform mobile app with complex subscription management supporting multiple regions and currencies. Implemented device-based authentication, in-app purchases for iOS and Android, quota management with timezone-aware calculations, and real-time WebHook processing for subscription events.
Tech -> React Native, Expo SDK 54, NodeJS, Express, MongoDB, Apple StoreKit, Google Play Billing
4. Real-Time Data Processing Pipeline - Architected a scalable async job processing system with SSE-based progress streaming, circuit breakers for external API resilience, distributed locking, and parallel processing workers. Handles thousands of requests daily with 99.9% uptime.
Tech -> FastAPI, Python asyncio, Redis, Docker, AWS Elastic Beanstalk
Steps for completing your project
After purchasing the project, send requirements so Gaurav can start the project.
Delivery time starts when Gaurav receives requirements from you.
Gaurav works on your project following the steps below.
Revisions may occur after the delivery date.
Discovery & Setup
Review your documents and requirements. Set up development environment and vector database.
Document Ingestion
Process and chunk your documents. Generate embeddings and index in vector database.