Aqdas A.

I build private AI systems that help teams search, understand, and act on their own data without sending sensitive information to third-party APIs. My work focuses on Retrieval-Augmented Generation (RAG), LLM applications, AI assistants, and automation workflows that run on your own servers, cloud VPC, or air-gapped environment. Clients hire me when they need an internal chatbot for documents and knowledge bases, secure AI search across PDFs and business data, or workflow automation that connects LLMs to databases and tools like SharePoint, Notion, Confluence, CRMs, and internal APIs. I design full RAG pipelines including document processing, chunking, embeddings, vector storage, retrieval, and response generation. My stack includes Python, LangChain, LlamaIndex, LangGraph, FastAPI, Ollama, vLLM, Pinecone, Weaviate, ChromaDB, pgvector, OpenAI, Claude, Mistral, and LLaMA. I also build REST APIs, webhooks, and production-ready deployments with Docker, testing, monitoring, and documentation. If you need a secure, practical AI solution built around your real business workflow, send me a message. I’ll help you figure out the right architecture and the fastest path to a working system.