Docer.to is an AI-powered platform designed to revolutionize document interaction. By enabling users to upload documents such as PDFs, DOCX, TXT, and various code files, it transforms static files into interactive experiences. Users can chat with their documents, retrieve information, ask questions, and collaborate in real-time. This tool makes documents more dynamic and productive, turning them into living entities that can be queried and understood effortlessly. Ideal for both individual users and businesses looking to enhance document handling and data extraction.

AlgoDocs is an intelligent document processing platform designed to automate the extraction of critical data from various document types such as PDFs, images, and text files. Utilizing advanced AI and machine learning, AlgoDocs offers a no-code solution perfect for businesses looking to save time, reduce errors, and improve data accuracy. The platform supports seamless integration, making it simple to validate and export data into your preferred formats or systems.

SmartRAG is a modular Python library designed for retrieval-augmented generation (RAG) workflows with large language models. It combines document ingestion, vector indexing, and state-of-the-art LLM APIs to deliver accurate, context-rich responses. Users can import PDFs, text files, or web pages, index them using popular vector stores like FAISS or Chroma, and define custom prompt templates. SmartRAG orchestrates the retrieval, prompt assembly, and LLM inference, returning coherent answers grounded in source documents. By abstracting the complexity of RAG pipelines, it accelerates development of knowledge base Q&A systems, chatbots, and research assistants. Developers can extend connectors, swap LLM providers, and fine-tune retrieval strategies to fit specific knowledge domains.