Cradl AI provides a robust AI-powered platform designed to simplify and automate your internal document workflows. With easy-to-train machine learning models, users can efficiently extract and process critical data from various document types (such as PDFs and images). The no-code platform can be integrated with popular automation tools, offering a seamless and flexible solution to significantly enhance productivity and accuracy in document management processes.

Doc2Cart is an API-first platform designed to automate extracting product information from documents. Utilizing advanced OCR technology, it processes PDFs and image files, transforming this data into structured formats suitable for various e-commerce platforms. Users upload their documents, wait for analysis, review and approve the extracted data, and then export it or integrate it directly into their systems via API. The platform is user-friendly, offering a document analysis wizard for ease of use.

DocChat-Docling is an AI document chatbot framework that transforms static documents into an interactive knowledge base. By ingesting PDFs, text files, and other formats, it indexes content with vector embeddings and enables natural language Q&A. Users can ask follow-up questions, and the agent retains context for accurate dialogue. Built on Python and leading LLM APIs, it offers scalable document processing, customizable pipelines, and easy integration, empowering teams to self-serve information without manual searches or complex queries.

DocGPT is designed to simplify information extraction and Q&A from documents by providing a seamless conversational interface. Users can upload documents in PDF, Word, or PowerPoint formats, which are then processed using text parsers. The content is chunked and embedded with OpenAI's embedding models, stored in a vector database like FAISS or Pinecone. When a user submits a query, DocGPT retrieves the most relevant text chunks via similarity search and leverages ChatGPT to generate accurate, context-aware responses. It features interactive chat, document summarization, customizable prompts for domain-specific needs, and is built on Python with a Streamlit UI for easy deployment and extensibility.

DocumentAI-Backend is a lightweight backend framework that automates extraction of text, form fields, and structured data from documents. It offers REST API endpoints for uploading PDFs or images, processes them via Google Document AI with OCR fallback, and returns parsed results in JSON. Built with Python, FastAPI, and Docker, it enables quick integration into existing systems, scalable deployments, and customization through configurable pipelines and middleware.