Shiza S.

AI chatbot and RAG developer. 6 projects delivered, 5 five-star reviews. Live demo: prime-care-sit.vercel.app , RAG chatbot trained on business documents with lead capture and admin panel. Built with OpenAI API, LangChain, Pinecone, Supabase pgvector. Next.js, FastAPI, React. 100% Job Success, Top Rated. Here's what my clients say: "Shiza did an excellent job. She is quick and smart with her work. Lightning speed work. Highly impressed and recommended." "She is reliable, fast, and understands business logic well. She doesn't just code but thinks through practical use cases and suggests better workflows." "Shiza is an outstanding professional with exceptional technical skill and excellent communication. She delivered the work to the highest possible standard." WHAT I BUILD AI Chatbots & RAG Systems Chatbots trained on your business data using RAG (retrieval augmented generation). Upload documents, the AI answers only from your content. Lead capture, intent detection, embeddable widgets. Built with OpenAI API, LangChain, Pinecone, and Supabase pgvector. Document Processing & Data Extraction PDF parsing, OCR, invoice processing, structured data output from messy inputs. Built an AI invoice management system that processes PDFs and automates reconciliation for a real business. Full-Stack Web Applications React/Next.js frontend, FastAPI or NestJS backend, PostgreSQL/Firebase/Supabase database. Authentication, dashboards, admin panels, role-based access. Clean architecture that other developers can extend. RECENT PROJECTS RAG AI Chatbot + Lead Capture (5-star review) Embeddable chatbot widget trained on business documents. Lead capture with buying-intent detection, email notifications with conversation context, admin panel for managing docs and viewing leads. Live at prime-care-sit.vercel.app AI Chatbot with OpenAI and Flowise (5-star review) Custom AI chatbot for a client's website. Trained on business content, responsive design, integrated with existing systems. AI Invoice Management System Processes PDF invoices, extracts structured data, automates reconciliation, generates business reports. FastAPI backend, Next.js frontend. AI Inventory Chatbot Natural language queries against a database. Users ask "show me low stock items" and get structured answers. Dynamic SQL generation with LangChain. Built both web (React) and mobile (Flutter) versions. RAG Pipeline for LMS Document ingestion, text chunking, OpenAI embeddings, Pinecone vector storage for semantic search across large document sets. TECH STACK Frontend: React, Next.js, Tailwind CSS Backend: Python (FastAPI, Django), Node.js, NestJS AI/LLM: OpenAI API, LangChain, RAG pipelines Vector DB: Pinecone, Supabase pgvector, ChromaDB Database: PostgreSQL, Firebase, Supabase Mobile: Flutter (iOS + Android) DevOps: Docker, AWS, Vercel BS in Artificial Intelligence, National University of Modern Languages.