You will get RAG Pipeline Development with Metadata-Aware Search and LLM Integration

Project details
🚀 AI-Powered RAG (Retrieval-Augmented Generation) Solutions
I specialize in building intelligent, end-to-end RAG systems using:
🔧 Tech Stack:
• Python + FastAPI – for clean, high-performance APIs
• OpenAI (GPT + Embeddings) – to power natural, context-aware responses
• Pinecone / Qdrant – fast, scalable vector search
• MongoDB (optional) – for storing metadata or structured content
🎯 What You Get:
• Custom RAG pipelines: chunking, embedding, retrieval, generation
• Domain-specific assistants & Q&A tools
• Smart search over documents, PDFs, and knowledge bases
• Secure, production-ready API integrations
• Optional web UI or chatbot interface if needed
Whether you need a smart chatbot, internal knowledge assistant, or AI-powered search system, I’ll deliver a tailored solution that turns your unstructured data into actionable insights.
I specialize in building intelligent, end-to-end RAG systems using:
🔧 Tech Stack:
• Python + FastAPI – for clean, high-performance APIs
• OpenAI (GPT + Embeddings) – to power natural, context-aware responses
• Pinecone / Qdrant – fast, scalable vector search
• MongoDB (optional) – for storing metadata or structured content
🎯 What You Get:
• Custom RAG pipelines: chunking, embedding, retrieval, generation
• Domain-specific assistants & Q&A tools
• Smart search over documents, PDFs, and knowledge bases
• Secure, production-ready API integrations
• Optional web UI or chatbot interface if needed
Whether you need a smart chatbot, internal knowledge assistant, or AI-powered search system, I’ll deliver a tailored solution that turns your unstructured data into actionable insights.
AI Algorithms
Autoencoder, Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Chatbot, Natural Language Generation, Natural Language UnderstandingAI Development Language
PythonAI Tools
Azure OpenAI, GitHub CopilotAI Models
ChatGPT, GPT-3, GPT-4What's included $250
These options are included with the project scope.
$250
- Delivery Time 5 days
- Number of Revisions 2
- AI Model Integration
- Batch Normalization
- Database Integration
- Detailed Code Comments
- Model Deployment
- Model Documentation
- Natural Language Processing
- Prompt Engineering
- Setup File
- Source Code
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SP
Stephen P.
Jun 12, 2025
Full Stack Software Engineer with AI Backend Expertise Needed
Ravi was great to work with good communication skills and daily syncs. He was able to set up a RAG POC for my AI pipelines.
About Ravi
Data Scientist II - Gen AI
Bengaluru, India - 3:38 am local time
Highly skilled in Python, SQL, Vector DB, GenAI, LLM’s, identifying gaps and insights, optimizing performance, implementing creative growth strategies, and leveraging generative AI technologies.
Steps for completing your project
After purchasing the project, send requirements so Ravi can start the project.
Delivery time starts when Ravi receives requirements from you.
Ravi works on your project following the steps below.
Revisions may occur after the delivery date.
Project kickoff and data review
I analyze your documents/data, plan chunking, embedding, and vector DB setup.
Development of RAG pipeline
Implement document processing, vector embedding, search setup, and LLM integration with OpenAI.