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Fiverr Pro
English
$
USD
I will develop rag for your business using langchain and openai
Ahmed S
About this gig
Need help boosting your AI's capabilities?
I specialize in creating advanced Retrieval-Augmented Generation (RAG) applications, including agentic RAG with LangChain/LangGraph and Crewai. I integrate top vector databases like Pinecone, Milvus, Chroma, and FAISS to ensure your AI provides accurate and relevant responses.
What I Offer:
- Custom RAG Application Development
- Agentic RAG with LangGraph & Crewai
- Integration with LangChain & Crewai
- Integration with Next.js for modern user interface
- Vector Database Integration: Pinecone, Milvus, Chroma, FAISS
- Frontend on Streamlit for Testing
- Enhanced AI Chatbots (e.g., Customer Support, E-commerce, Legal, Education, Finance, Travel, and Real Estate)
What I Need from You:
- OpenAI API Key
- Documents
Lets solve your AI challenges together. Contact me before placing an order!
Get to know Ahmed S
Ahmed S
Cloud Native Full stack Agentic AI Engineer
- FromPakistan
- Member sinceAug 2021
- Avg. response time1 hour
- Last delivery6 months
Languages
Urdu, English
Top 5% Cloud-Native & AI-Native Engineer specializing in Agentic AI systems that can handle users up to 100M. I build next-gen autonomous applications using OpenAI Agent SDK, LangGraph, and Claude Code CLI / OpenAI Codex integrated with MCP servers — enabling fully automated, high-speed development pipelines. As both an expert Prompt Engineer and advanced Context Engineer, I design precise, instruction- and knowledge-driven interactions that maximize LLM reasoning and reliability. Skilled across the full stack (Next.js, FastAPI, PostgreSQL, Pinecone), I deliver scalable, event-driven architect
My Portfolio
FAQ
What is a Retrieval-Augmented Generation (RAG) application?
RAG applications combine traditional information retrieval with advanced AI text generation to provide more accurate and contextually relevant responses. This helps your AI retrieve and generate information based on a large database or vector storage.
What is Agentic RAG, and how does it differ from regular RAG?
Agentic RAG involves using agentic workflows, which allows the AI to perform complex tasks like decision-making and task automation. It’s more advanced than regular RAG because it adapts to specific user goals and provides more intelligent, goal-driven responses.
Do I need an OpenAI API key for my RAG application?
Yes, to generate AI-based responses, you’ll need an OpenAI API key. I’ll guide you on how to get it and integrate it into your application.
How do you test the AI chatbot before finalizing the development?
I use Streamlit to create a user-friendly frontend for testing, allowing you to interact with the chatbot, test its functionalities, and ensure everything works smoothly before deployment.
What are the benefits of using Pinecone for vector databases?
Pinecone offers fast, scalable, and reliable vector search, ensuring that your AI can retrieve the most relevant information quickly. It simplifies the integration process and enhances the performance of your RAG application, providing high accuracy and low latency.
