Best AI tools for< Organize Documents >

Keepi is a personal knowledge AI application that allows users to capture, organize, and retrieve their knowledge effortlessly. With Keepi, users can capture ideas, URLs, documents, and images, and the application uses AI to enrich and organize this knowledge for easy retrieval. Users can access their personal knowledge on the go or in the office, leveraging their insights. Keepi.ai has received positive feedback from clients who appreciate its ability to save time, provide wisdom, and even draw pictures. The application aims to unlock the full potential of users' knowledge and enhance their productivity.

Immplify is the ultimate platform for immigrants, offering an advanced document management system, on-demand immigration-related services, and a vibrant verified immigrant community. The platform ensures advanced security for user documents through 2-factor authentication, data redaction, AES 256-bit encryption, and tokenization of sensitive information. Immplify simplifies the immigration process by providing features like digitizing documents, on-the-go scanning, lock-tight security, auto-organization, travel time tracking, intelligent document tracking, key insights dashboard, instant access to immigration guidance, and secure document sharing. Trusted by immigrants, Immplify streamlines document management, travel history tracking, visa form filling, and overall organization, making it a valuable tool for immigrants in the USA.

Slite is an AI-powered knowledge base application designed to help teams organize, collaborate, and access information efficiently. It offers a user-friendly interface, hassle-free adoption, and AI-powered search capabilities. With features like document creation, AI-driven question-answering, templates, integrations, and multi-platform support, Slite aims to streamline knowledge management for various departments such as Product & Engineering, Customer Support, Human Resources, IT & Operations. The application is trusted by over 200,000 leading companies as their single source of truth, providing personalized onboarding, dedicated support, and a thriving product community.

RealtyGenius.AI is an AI-powered real estate assistant that revolutionizes document management in the real estate industry. It allows users to upload and organize documents seamlessly, chat with them as if they're human, and collaborate with teams effortlessly. The tool ensures end-to-end encryption for document security, provides instant and perfect memory for all documents, and offers features like easy organization and categorization of real estate documents.

Petal is a document analysis platform powered by generative AI technology. It allows users to chat with their documents, providing fully sourced and reliable answers by linking to their own knowledge bases. Users can train AI on their documents to support their work, ensuring centralized knowledge management and document synchronization. Petal offers features such as automatic metadata extraction, file deduplication, and collaboration tools to enhance productivity and streamline workflows for researchers, faculty, and industry experts.

Knowledge Drive is the world's only self-organizing, self-maintaining, and fully integrated work knowledge system. It utilizes AI technology to automatically build a knowledge base by extracting useful information from documents. The system ensures knowledge freshness, easy access to information, and seamless integration across various platforms like Microsoft Office 365, Google Workspace, and Slack. Knowledge Drive aims to revolutionize knowledge management and boost productivity in teams by providing a central source of truth and eliminating the need for manual documentation.

Grok is an AI-powered search engine that helps you find the documents you need quickly and easily. With Grok, you can search across all of your files, emails, and chats, and get instant results. Grok also uses AI to learn your search habits and preferences, so the more you use it, the better it gets at finding the documents you need.

docbot is an AI-powered tool that allows users to interact with their documents using natural language. Users can create bots, upload documents, share websites, or add text to build knowledge bases and ask questions. The tool supports a wide range of document formats and prioritizes a collaborative, mobile-first experience. docbot simplifies document understanding and management by leveraging AI technology to provide users with a seamless and secure platform for document interaction.

SubEasy is a next-generation AI-powered subtitle and transcription platform that offers accurate transcriptions, precise translations, and context-aware subtitle segmentations. It provides a complete solution for creating subtitles and videos with customizable styles and one-click export options. Users can collaborate in real-time, organize documents, and enjoy fast transcription services. SubEasy is trusted by thousands of users for its efficiency in translating event content, boosting content reach, and improving subtitle generation workflows.

Legaliser is an AI legal assistant that revolutionizes contract management by providing comprehensive AI analysis, intuitive drafting tools, and a diverse range of customizable templates. It quickly summarizes contracts, evaluates clauses for compliance, and offers targeted suggestions to enhance contract clarity and compliance. Legaliser streamlines document management with AI-driven summaries, clause ratings, and smart organization, making it an indispensable tool for legal professionals across diverse industries.

NotebookLM is an AI-powered note-taking and research assistant that leverages Google's Gemini 1.5 Pro model. It helps users organize and analyze information from uploaded documents, providing personalized insights and in-line citations. NotebookLM prioritizes user privacy by not using personal data to train its AI, ensuring the security of sensitive information. The application is designed to assist users in transforming information into actionable insights efficiently and collaboratively.

Skann AI is an advanced artificial intelligence tool designed to revolutionize document management and data extraction processes. The application leverages cutting-edge AI technology to automate the extraction of data from various documents, such as invoices, receipts, and contracts. Skann AI streamlines workflows, increases efficiency, and reduces manual errors by accurately extracting and organizing data in a fraction of the time it would take a human. With its intuitive interface and powerful features, Skann AI is the go-to solution for businesses looking to optimize their document processing workflows.

Matey AI is an advanced AI application designed to empower legal teams with cutting-edge AI technologies for document classification, document review, outcome prediction, automated trial preparation, and more. The platform leverages AI expertise and legal expertise to provide efficient solutions for legal practices of all sizes, ensuring data security, compliance, and seamless integration with existing legal workflows.

The Local File Organizer is an AI-powered tool designed to help users organize their digital files efficiently and securely on their local device. By leveraging advanced AI models for text and visual content analysis, the tool automatically scans and categorizes files, generates relevant descriptions and filenames, and organizes them into a new directory structure. All AI processing occurs locally using the Nexa SDK, ensuring privacy and security. With support for multiple file types and customizable prompts, this tool aims to simplify file management and bring order to users' digital lives.

Basdonax AI RAG v1.0 is a repository that contains all the necessary resources to create your own AI-powered secretary using the RAG from Basdonax AI. It leverages open-source models from Meta and Microsoft, namely 'Llama3-7b' and 'Phi3-4b', allowing users to upload documents and make queries. This tool aims to simplify life for individuals by harnessing the power of AI. The installation process involves choosing between different data models based on GPU capabilities, setting up Docker, pulling the desired model, and customizing the assistant prompt file. Once installed, users can access the RAG through a local link and enjoy its functionalities.

Notate is a powerful desktop research assistant that combines AI-driven analysis with advanced vector search technology. It streamlines research workflow by processing, organizing, and retrieving information from documents, audio, and text. Notate offers flexible AI capabilities with support for various LLM providers and local models, ensuring data privacy. Built for researchers, academics, and knowledge workers, it features real-time collaboration, accessible UI, and cross-platform compatibility.

Uwazi is a flexible database application designed for capturing and organizing collections of information, with a focus on document management. It is developed and supported by HURIDOCS, benefiting human rights organizations globally. The tool requires NodeJs, ElasticSearch, ICU Analysis Plugin, MongoDB, Yarn, and pdftotext for installation. It offers production and development installation guides, including Docker setup. Uwazi supports hot reloading, unit and integration testing with JEST, and end-to-end testing with Nightmare or Puppeteer. The system requirements include RAM, CPU, and disk space recommendations for on-premises and development usage.

Cognita is an open-source framework to organize your RAG codebase along with a frontend to play around with different RAG customizations. It provides a simple way to organize your codebase so that it becomes easy to test it locally while also being able to deploy it in a production ready environment. The key issues that arise while productionizing RAG system from a Jupyter Notebook are: 1. **Chunking and Embedding Job** : The chunking and embedding code usually needs to be abstracted out and deployed as a job. Sometimes the job will need to run on a schedule or be trigerred via an event to keep the data updated. 2. **Query Service** : The code that generates the answer from the query needs to be wrapped up in a api server like FastAPI and should be deployed as a service. This service should be able to handle multiple queries at the same time and also autoscale with higher traffic. 3. **LLM / Embedding Model Deployment** : Often times, if we are using open-source models, we load the model in the Jupyter notebook. This will need to be hosted as a separate service in production and model will need to be called as an API. 4. **Vector DB deployment** : Most testing happens on vector DBs in memory or on disk. However, in production, the DBs need to be deployed in a more scalable and reliable way. Cognita makes it really easy to customize and experiment everything about a RAG system and still be able to deploy it in a good way. It also ships with a UI that makes it easier to try out different RAG configurations and see the results in real time. You can use it locally or with/without using any Truefoundry components. However, using Truefoundry components makes it easier to test different models and deploy the system in a scalable way. Cognita allows you to host multiple RAG systems using one app. ### Advantages of using Cognita are: 1. A central reusable repository of parsers, loaders, embedders and retrievers. 2. Ability for non-technical users to play with UI - Upload documents and perform QnA using modules built by the development team. 3. Fully API driven - which allows integration with other systems. > If you use Cognita with Truefoundry AI Gateway, you can get logging, metrics and feedback mechanism for your user queries. ### Features: 1. Support for multiple document retrievers that use `Similarity Search`, `Query Decompostion`, `Document Reranking`, etc 2. Support for SOTA OpenSource embeddings and reranking from `mixedbread-ai` 3. Support for using LLMs using `Ollama` 4. Support for incremental indexing that ingests entire documents in batches (reduces compute burden), keeps track of already indexed documents and prevents re-indexing of those docs.

The Second Brain AI Agent Project is a tool designed to empower personal knowledge management by automatically indexing markdown files and links, providing a smart search engine powered by OpenAI, integrating seamlessly with different note-taking methods, and enhancing productivity by accessing information efficiently. The system is built on LangChain framework and ChromaDB vector store, utilizing a pipeline to process markdown files and extract text and links for indexing. It employs a Retrieval-augmented generation (RAG) process to provide context for asking questions to the large language model. The tool is beneficial for professionals, students, researchers, and creatives looking to streamline workflows, improve study sessions, delve deep into research, and organize thoughts and ideas effortlessly.

HippoRAG is a novel retrieval augmented generation (RAG) framework inspired by the neurobiology of human long-term memory that enables Large Language Models (LLMs) to continuously integrate knowledge across external documents. It provides RAG systems with capabilities that usually require a costly and high-latency iterative LLM pipeline for only a fraction of the computational cost. The tool facilitates setting up retrieval corpus, indexing, and retrieval processes for LLMs, offering flexibility in choosing different online LLM APIs or offline LLM deployments through LangChain integration. Users can run retrieval on pre-defined queries or integrate directly with the HippoRAG API. The tool also supports reproducibility of experiments and provides data, baselines, and hyperparameter tuning scripts for research purposes.

paperless-gpt is a tool designed to generate accurate and meaningful document titles and tags for paperless-ngx using Large Language Models (LLMs). It supports multiple LLM providers, including OpenAI and Ollama. With paperless-gpt, you can streamline your document management by automatically suggesting appropriate titles and tags based on the content of your scanned documents. The tool offers features like multiple LLM support, customizable prompts, easy integration with paperless-ngx, user-friendly interface for reviewing and applying suggestions, dockerized deployment, automatic document processing, and an experimental OCR feature.

PaperQA is a minimal package for question and answering from PDFs or text files, providing very good answers with in-text citations. It uses OpenAI Embeddings to embed and search documents, and follows a process of embedding docs and queries, searching for top passages, creating summaries, scoring and selecting relevant summaries, putting summaries into prompt, and generating answers. Users can customize prompts and use various models for embeddings and LLMs. The tool can be used asynchronously and supports adding documents from paths, files, or URLs.

PaperQA is a minimal package for question and answering from PDFs or text files, providing very good answers with in-text citations. It uses OpenAI Embeddings to embed and search documents, and includes a process of embedding docs, queries, searching for top passages, creating summaries, using an LLM to re-score and select relevant summaries, putting summaries into prompt, and generating answers. The tool can be used to answer specific questions related to scientific research by leveraging citations and relevant passages from documents.

Instrukt is a terminal-based AI integrated environment that allows users to create and instruct modular AI agents, generate document indexes for question-answering, and attach tools to any agent. It provides a platform for users to interact with AI agents in natural language and run them inside secure containers for performing tasks. The tool supports custom AI agents, chat with code and documents, tools customization, prompt console for quick interaction, LangChain ecosystem integration, secure containers for agent execution, and developer console for debugging and introspection. Instrukt aims to make AI accessible to everyone by providing tools that empower users without relying on external APIs and services.

5ire is a cross-platform desktop client that integrates a local knowledge base for multilingual vectorization, supports parsing and vectorization of various document formats, offers usage analytics to track API spending, provides a prompts library for creating and organizing prompts with variable support, allows bookmarking of conversations, and enables quick keyword searches across conversations. It is licensed under the GNU General Public License version 3.

Awesome-Colorful-LLM is a meticulously assembled anthology of vibrant multimodal research focusing on advancements propelled by large language models (LLMs) in domains such as Vision, Audio, Agent, Robotics, and Fundamental Sciences like Mathematics. The repository contains curated collections of works, datasets, benchmarks, projects, and tools related to LLMs and multimodal learning. It serves as a comprehensive resource for researchers and practitioners interested in exploring the intersection of language models and various modalities for tasks like image understanding, video pretraining, 3D modeling, document understanding, audio analysis, agent learning, robotic applications, and mathematical research.

LLMWare is a framework for quickly developing LLM-based applications including Retrieval Augmented Generation (RAG) and Multi-Step Orchestration of Agent Workflows. This project provides a comprehensive set of tools that anyone can use - from a beginner to the most sophisticated AI developer - to rapidly build industrial-grade, knowledge-based enterprise LLM applications. Our specific focus is on making it easy to integrate open source small specialized models and connecting enterprise knowledge safely and securely.

Kernel Memory (KM) is a multi-modal AI Service specialized in the efficient indexing of datasets through custom continuous data hybrid pipelines, with support for Retrieval Augmented Generation (RAG), synthetic memory, prompt engineering, and custom semantic memory processing. KM is available as a Web Service, as a Docker container, a Plugin for ChatGPT/Copilot/Semantic Kernel, and as a .NET library for embedded applications. Utilizing advanced embeddings and LLMs, the system enables Natural Language querying for obtaining answers from the indexed data, complete with citations and links to the original sources. Designed for seamless integration as a Plugin with Semantic Kernel, Microsoft Copilot and ChatGPT, Kernel Memory enhances data-driven features in applications built for most popular AI platforms.

STORM is a LLM system that writes Wikipedia-like articles from scratch based on Internet search. While the system cannot produce publication-ready articles that often require a significant number of edits, experienced Wikipedia editors have found it helpful in their pre-writing stage. **Try out our [live research preview](https://storm.genie.stanford.edu/) to see how STORM can help your knowledge exploration journey and please provide feedback to help us improve the system 🙏!**

The Artificial Intelligence Incident Database (AIID) is a collection of incidents involving the development and use of artificial intelligence (AI). The database is designed to help researchers, policymakers, and the public understand the potential risks and benefits of AI, and to inform the development of policies and practices to mitigate the risks and promote the benefits of AI. The AIID is a collaborative project involving researchers from the University of California, Berkeley, the University of Washington, and the University of Toronto.

A massive list including a huge amount of products and services that are completely free! ⭐ Star on GitHub • 🤝 Contribute # Table of Contents * APIs, Data & ML * Artificial Intelligence * BaaS * Code Editors * Code Generation * DNS * Databases * Design & UI * Domains * Email * Font * For Students * Forms * Linux Distributions * Messaging & Streaming * PaaS * Payments & Billing * SSL

Pathway's LLM (Large Language Model) Apps provide a platform to quickly deploy AI applications using the latest knowledge from data sources. The Python application examples in this repository are Docker-ready, exposing an HTTP API to the frontend. These apps utilize the Pathway framework for data synchronization, API serving, and low-latency data processing without the need for additional infrastructure dependencies. They connect to document data sources like S3, Google Drive, and Sharepoint, offering features like real-time data syncing, easy alert setup, scalability, monitoring, security, and unification of application logic.

OpenDAN is an open source Personal AI OS that consolidates various AI modules for personal use. It empowers users to create powerful AI agents like assistants, tutors, and companions. The OS allows agents to collaborate, integrate with services, and control smart devices. OpenDAN offers features like rapid installation, AI agent customization, connectivity via Telegram/Email, building a local knowledge base, distributed AI computing, and more. It aims to simplify life by putting AI in users' hands. The project is in early stages with ongoing development and future plans for user and kernel mode separation, home IoT device control, and an official OpenDAN SDK release.

作为教师，我整理教学文档并提供详细解答。

An Operations Department Assistant aids the operations team by handling administrative tasks, process documentation, and data analysis, helping to streamline and optimize various operational processes within an organization.

I create structured filenames for PDFs from OCR text.

Expert in OCR and document formatting, with a focus on professionalism.

Turns company financial documents into structured income statements.

myaidrive.com plugin to search across all your dive documents.

Connect and interact with your Google accounts. Organize, retrieve, and manipulate data with A.I

Experto en organizar información en formato de texto combinado.

Helps annotate project guidelines.

Helps users manage and preserve family heirlooms with empathy and practical advice.

Assistant to help researchers with thesis research and documentation process.

Specialist in sorting ancient Chinese medicine literature.

Novel editor with a serene style.

Responds to all queries with a specific URL

Expert in detailed software documentation writing

I'm your Keeper of Arcane Lore, guiding you through eldritch mysteries.

Process Documentation for serving GPTs.

Sofistikert FAU-assistent for dokumenthåndtering, møte-organisering med integrert skolehelsetjenesten som kilde til veil for foreldre om barnas velferd (mobbing, kroppspress osv). Auto-generering av referater & agendaer vha 'speech2text'-funksjon med strenge GDPR protokoller for opptak-sletting ++

Write Excellent Medical Notes

简洁懒人化Markdown笔记助手