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$
USD
I will develop rag pipelines, ai chatbots, and finetune llms
Nabeel
About this gig
Are you looking for a production-ready RAG pipeline, custom AI chatbot, or fine-tuned LLM built for your use case? You're in the right place.
I build end-to-end Generative AI solutions using LangChain, LlamaIndex, LangGraph, OpenAI, and Python, always ensuring they are scalable, reliable, and ready to go live.
What I Build:
RAG Systems: answers in your data using Pinecone, ChromaDB, FAISS, or Milvus AI Chatbots smart assistants powered by GPT-4, Claude, Gemini, LLaMA, DeepSeek or Groq AI
Agents & Agentic AI: autonomous systems that browse, reason, and complete multi-step tasks
LLM Fine-Tuning: a model trained on your domain that outperforms generic AI out of the box
Document Q&A: instantly search and extracts insights from PDFs, CSVs, and Word files. FastAPI Backends is a live, scalable AI API your team or product can plug into immediately.
Why Choose Me:
- Solutions built to scale with your business, AI that solves a real problem.
- Fast delivery with clear daily communication
- Revisions until you're 100% satisfied
- End-to-end support from development to deployment
Have a unique AI idea? Message me before placing an order
Get to know Nabeel
Nabeel
Full Stack AI and Web3 Developer
- FromPakistan
- Member sinceApr 2021
- Avg. response time1 hour
- Last delivery4 months
Languages
Urdu, English
A full-stack AI & Web3 Developer with 4 years of experience in Artificial Intelligence and Web3. Experienced in applying AI techniques like machine learning and natural language processing to improve blockchain protocols, automate workflows, and enable data-driven decision-making. Focused on advancing decentralized ecosystems through the integration of Web3 and AI technologies.
My Portfolio
FAQ
What types of RAG pipelines and AI chatbots can you build?
build document Q&A chatbots, customer support bots, internal knowledge base assistants, and multi-source RAG systems using LangChain, LlamaIndex, and LangGraph. I integrate any LLM including GPT-4, Claude, Gemini, LLaMA, DeepSeek, and Groq with vector databases like Pinecone, ChromaDB, and FAISS.
Can you fine-tune an LLM on my own data?
es. I fine-tune open-source models like LLaMA, Mistral, and Falcon on your custom dataset using LoRA, QLoRA, and PEFT with HuggingFace Transformers, giving you a domain-specific model that outperforms generic AI on your exact use case.
Do you build AI agents and agentic AI workflows?
Absolutely. I build autonomous AI agents using LangGraph, CrewAI, and AutoGen that browse the web, call external APIs, use tools, maintain memory, and complete complex multi-step tasks without human input at each step.
What documents and data sources can the chatbot work with?
PDFs, Word documents, Excel/CSV files, PowerPoint, plain text, web URLs, SQL databases, and REST APIs. Your chatbot retrieves accurate, cited answers from any of these using advanced retrieval and reranking techniques.
Do you work with open-source LLMs or only OpenAI?
Both. I work with OpenAI GPT-4, Anthropic Claude, and Google Gemini as well as fully open-source models like LLaMA, Mistral, DeepSeek, Phi, and Qwen via Ollama or HuggingFace, giving you full flexibility on cost, privacy, and performance.
What vector databases and embedding models do you support?
I support Pinecone, ChromaDB, FAISS, Milvus, and Weaviate. For embeddings I use OpenAI Embeddings, HuggingFace sentence transformers, and Cohere
Do I need to share my API keys or credentials
You provide your own API keys so you stay in full control of costs and data. I never store or reuse your credentials. If you prefer a fully self-hosted solution with no external API dependencies, I can build that too using Ollama or locally deployed HuggingFace models.
