selfGPT

selfGPT is an AI summarizer tool that turns your PDFs and files into AI insights. selfGPT is a RAG-based assistant that indexes your PDFs and text files so you can ask questions, get summaries, and extract insights from your own documents.

selfGPT is a retrieval-augmented generation (RAG) service that turns your own documents into a question-answering assistant. You upload PDFs or text files, the system indexes them, and then you can ask questions, request summaries, or have key information extracted. The tool is built for people who need to work through dense material quickly: researchers, analysts, students, and professionals who regularly handle long reports, contracts, or papers and want answers grounded in those specific files rather than generic model output. In practice you start by uploading a PDF or text file through the web app. selfGPT processes the document, extracting text and images, and builds a searchable index. From there you interact in a chat-style interface: ask for a summary of a section, request an explanation of a complex passage, or query across the content. The system retrieves relevant parts of your document to generate contextual responses, so the answers stay tied to your source material. A separate capability lets you chat with YouTube videos by supplying a URL, which is useful for extracting key concepts from long talks or tutorials without watching them in full. Where selfGPT differs from general chatbots is its focus on document grounding. Instead of pasting text into a general assistant and hoping it retains context, the RAG pipeline indexes your files and retrieves the right passages on demand. Compared with heavier enterprise document platforms, it is lighter and priced per operation rather than by seat. The micro-transaction model means you pay for prompts, completions, embeddings, and annotations as you use them, with usage visible inside the app. For individuals and small teams that want targeted document analysis without a large subscription, that structure is the main draw. The trade-off is that advanced workflow features and broad format support are limited, so it suits focused document Q&A more than full-scale data analysis or multi-source pipelines.