Best AI tools for< Retrieve Knowledge >

Keepi is a personal knowledge AI application designed to help users capture, organize, and retrieve their knowledge effortlessly. With Keepi, users can capture ideas, documents, and images, and the application uses AI to enrich and organize this knowledge for easy access. Users can leverage their personal knowledge on the go or in the office, making it a valuable tool for enhancing productivity and efficiency. Keepi also offers features such as insights creation, voice message transcription, and drawing capabilities, providing a comprehensive solution for managing and utilizing personal knowledge.

MyMemo is an AI-powered knowledge management tool that helps users organize, analyze, and retrieve their digital knowledge. It uses natural language processing and machine learning to understand the content of users' uploads, extract key insights, and generate summaries. MyMemo also allows users to create collections of memos, ask questions to the AI, and collaborate with others. It is designed to help users save time, improve their productivity, and make better use of their knowledge.

ChatGent is an advanced AI-powered professional assistant builder that revolutionizes the way professionals manage their interactions and tasks. It leverages the latest GPT models to provide high-quality, contextually relevant responses and robust security measures. ChatGent transforms complex data into simple, actionable conversations, enhancing productivity, efficiency, and decision-making for professionals across various industries.

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.

GoLinks® is an AI-driven platform that offers instant access to internal knowledge through short links. It empowers teams to retrieve and share information quickly, improving collaboration and productivity. With features like AI-powered resource search, team knowledge library, mobile apps, and analytics, GoLinks® streamlines workplace communication and efficiency. The platform caters to various industries and team sizes, providing enterprise-grade security and integrations with popular work tools. Customers trust GoLinks® to save time, money, and enhance collaboration across departments.

Mindset AI is an AI tool that enables users to create AI agents in seconds using simple language. It helps speed up teams' work by allowing the creation of AI agents without the need for coding. Users can write, retrieve information, brainstorm, and more securely using their company's knowledge in a collaborative workspace. Mindset AI offers features such as AI agent builder, integrated knowledge banks, guided conversational search, capabilities for process description, and AI model selector.

Ubblu is an AI-driven note-taking application that aims to help users search less and create more by providing a seamless experience for capturing, organizing, and retrieving ideas and information. It offers features like note capture, card writing, tag categorization, instant knowledge retrieval, and 'Ask' functionality for quick access to stored information. Ubblu is designed to liberate users' minds from information retention, allowing them to focus on innovation and creativity. The application is desktop-based with a mobile version in development.

MemFree is a hybrid AI search tool that allows users to search for information instantly and receive accurate answers from the internet, bookmarks, notes, and documents. With MemFree, users can easily index their bookmarks and web pages with just one click. The tool leverages GPT-4o mini for enhanced search capabilities, making it a powerful and efficient AI application for information retrieval.

adam.ai is an AI-powered assistant for meeting management that offers enterprise-level intelligence to drive ROI. It provides a secure and intelligent platform for managing meetings, designed for boards, committees, and projects. The platform empowers directors and executives to document, retrieve, and act on meeting content, enhancing decision-making and organizational ROI.

Phew AI Tab is an AI-powered tab management tool that helps users organize and retrieve tab information efficiently. It utilizes AI-based grouping and spaces in a vertical sidebar to streamline tab management. With features like AI Grouping & Auto Collapse, AI Analyzing, AI Search, and AI-based Space & Cloud Sync, Phew AI Tab aims to enhance productivity and user experience. The tool ensures privacy with military-grade protection and offers seamless synchronization across devices.

Pinecone is a vector database designed to build knowledgeable AI applications. It offers a serverless platform with high capacity and low cost, enabling users to perform low-latency vector search for various AI tasks. Pinecone is easy to start and scale, allowing users to create an account, upload vector embeddings, and retrieve relevant data quickly. The platform combines vector search with metadata filters and keyword boosting for better application performance. Pinecone is secure, reliable, and cloud-native, making it suitable for powering mission-critical AI applications.

Gen AI For Enterprise is an AI application that offers a secure, scalable, and customizable platform for enterprises. It provides a private chat feature, enhanced knowledge retrieval, and custom business case development. The application is trusted by various industries and empowers teams to work better by leveraging advanced AI models and APIs. It ensures robust security, compliance with industry standards, and simplified user management. Gen AI For Enterprise aims to transform businesses by providing innovative AI solutions.

IntelliumAI is a leading AI application provider specializing in secure AI solutions for data-sensitive industries. Their flagship AI-powered assistant, BoostBot, empowers organizations to unlock their knowledge potential securely. Additionally, AiBoost offers a comprehensive AI platform tailored for advanced engineering professionals, enabling teams to leverage powerful AI capabilities without extensive data science expertise. IntelliumAI is trusted by industry leaders for its transparent and compliance-ready AI solutions.

Octoparse is an AI web scraping tool that offers a no-coding solution for turning web pages into structured data with just a few clicks. It provides users with the ability to build reliable web scrapers without any coding knowledge, thanks to its intuitive workflow designer. With features like AI assistance, automation, and template libraries, Octoparse is a powerful tool for data extraction and analysis across various industries.

FPrime AI is an AI application that aims to redefine Artificial Intelligence for enterprises by bridging the AI gap and empowering organizations of all sizes to leverage the transformative potential of AI. The application addresses common challenges such as the lack of AI vision, difficulty in finding and retaining AI talent, and data dilemmas. FPrime AI follows a customer-centric approach to tailor AI solutions, provide continuous support, and democratize access to AI knowledge and applications. The solution includes advanced AI technologies, automation tools, and analytics capabilities, with a team of AI experts and domain specialists collaborating closely with clients to address industry-specific needs and goals.

SOMA is a Research Automation Platform that accelerates medical innovation by providing up to 100x speedup through process automation. The platform collates and analyzes medical research articles, extracting important concepts and identifying causal and associative relationships between them. It organizes this information into a specialized database forming a knowledge graph. Researchers can retrieve causal chains, access specific research articles, and perform tasks like concept analysis, drug repurposing, and target discovery. SOMA enhances literature review by finding relevant articles based on the mechanism of action, saving time on organizing reviews and allowing researchers to focus on their own research. The platform offers freemium access with basic functionality for free indefinitely, with the option to subscribe to advanced features after a 14-day trial period.

ChatTube AI is an AI-powered platform that allows users to chat with YouTube videos and PDF documents, engage with interactive content, and generate quizzes for a smarter learning experience. It offers features such as real-time Q&A with videos, interactive PDF engagement, effortless quiz creation, and supports various use cases like distance learning, corporate training, content creation, and research and development. The platform provides powerful features for efficient information retrieval, easy quiz creation, and integrated learning tools, making learning interactive and engaging.

Glean is an AI-powered work assistant that helps teams harness generative AI and make better decisions faster. It connects all of your company's data across all of the content, people, and interactions in your organization. Glean's advanced personalization ensures that answers are tailored to who you are, who you work with, and what you're working on. Its Retrieval Augmented Generation (RAG) retrieves the most relevant information and ensures that LLMs answer with the most up-to-date knowledge.

Hypertype is an AI-powered email assistant that helps businesses save time and improve the quality of their customer communications. It automatically drafts emails with the most relevant information retrieved from your data, in seconds. This can save you up to 70% of the time you spend drafting emails, and it can also help you to provide more personalized and effective responses to your customers. Hypertype is used by over 2,000 businesses worldwide, and it has been featured in Forbes, The Wall Street Journal, and The New York Times.

Sapling is a language model copilot and API for businesses. It provides real-time suggestions to help sales, support, and success teams more efficiently compose personalized responses. Sapling also offers a variety of features to help businesses improve their customer service, including: * Autocomplete Everywhere: Provides deep learning-powered autocomplete suggestions across all messaging platforms, allowing agents to compose replies more quickly. * Sapling Suggest: Retrieves relevant responses from a team response bank and allows agents to respond more quickly to customer inquiries by simply clicking on suggested responses in real time. * Snippet macros: Allow for quick insertion of common responses. * Grammar and language quality improvements: Sapling catches 60% more language quality issues than other spelling and grammar checkers using a machine learning system trained on millions of English sentences. * Enterprise teams can define custom settings for compliance and content governance. * Distribute knowledge: Ensure team knowledge is shared in a snippet library accessible on all your web applications. * Perform blazing fast search on your knowledge library for compliance, upselling, training, and onboarding.

ChatPDF is a knowledge question and answer retrieval tool based on local LLM. It supports various open-source LLM models like ChatGLM3-6b, Chinese-LLaMA-Alpaca-2, Baichuan, YI, and multiple file formats including PDF, docx, markdown, txt. The tool optimizes RAG accuracy, Chinese chunk segmentation, embedding using text2vec's sentence embedding, retrieval matching with rank_BM25, and introduces reranker module for reranking candidate sets. It also enhances candidate chunk extension context, supports custom RAG models, and provides a Gradio-based RAG conversation page for seamless dialogue.

UnionLLM is a lightweight open-source Python toolkit that provides a unified way to access various domestic and foreign large language models and Agent orchestration tools compatible with OpenAI. It aims to connect various large language models in a unified and easily extensible way, making it more convenient to use multiple large language models. UnionLLM currently supports various domestic large language models and Agent orchestration tools, as well as over 100 models through LiteLLM, including models from major overseas language model developers and cloud service providers. It simplifies the process of calling different models by providing a consistent interface and expanding the returned information to include context for knowledge base retrieval.

KG-LLM-Papers is a repository that collects papers integrating knowledge graphs (KGs) and large language models (LLMs). It serves as a comprehensive resource for research on the role of KGs in the era of LLMs, covering surveys, methods, and resources related to this integration.

OP Vault is a tool that leverages the OP Stack (OpenAI + Pinecone Vector Database) to allow users to upload custom knowledgebase files and ask questions about their contents. It provides a user-friendly Golang server and React frontend for querying human-readable content like books and documents, making it valuable for knowledge extraction and question-answering. Users can upload entire libraries, receive specific answers with file and section references, and explore the power of the OP Stack in a practical interface.

The Keras-llm-robot Web UI project is an open-source tool designed for offline deployment and testing of various open-source models from the Hugging Face website. It allows users to combine multiple models through configuration to achieve functionalities like multimodal, RAG, Agent, and more. The project consists of three main interfaces: chat interface for language models, configuration interface for loading models, and tools & agent interface for auxiliary models. Users can interact with the language model through text, voice, and image inputs, and the tool supports features like model loading, quantization, fine-tuning, role-playing, code interpretation, speech recognition, image recognition, network search engine, and function calling.

Llama-github is a powerful tool that helps retrieve relevant code snippets, issues, and repository information from GitHub based on queries. It empowers AI agents and developers to solve coding tasks efficiently. With features like intelligent GitHub retrieval, repository pool caching, LLM-powered question analysis, and comprehensive context generation, llama-github excels at providing valuable knowledge context for development needs. It supports asynchronous processing, flexible LLM integration, robust authentication options, and logging/error handling for smooth operations and troubleshooting. The vision is to seamlessly integrate with GitHub for AI-driven development solutions, while the roadmap focuses on empowering LLMs to automatically resolve complex coding tasks.

A collection of papers related to knowledge distillation of large language models (LLMs). The repository focuses on techniques to transfer advanced capabilities from proprietary LLMs to smaller models, compress open-source LLMs, and refine their performance. It covers various aspects of knowledge distillation, including algorithms, skill distillation, verticalization distillation in fields like law, medical & healthcare, finance, science, and miscellaneous domains. The repository provides a comprehensive overview of the research in the area of knowledge distillation of LLMs.

This course has 18 lessons. Each lesson covers its own topic so start wherever you like! Lessons are labeled either "Learn" lessons explaining a Generative AI concept or "Build" lessons that explain a concept and code examples in both **Python** and **TypeScript** when possible. Each lesson also includes a "Keep Learning" section with additional learning tools. **What You Need** * Access to the Azure OpenAI Service **OR** OpenAI API - _Only required to complete coding lessons_ * Basic knowledge of Python or Typescript is helpful - *For absolute beginners check out these Python and TypeScript courses. * A Github account to fork this entire repo to your own GitHub account We have created a **Course Setup** lesson to help you with setting up your development environment. Don't forget to star (🌟) this repo to find it easier later. ## 🧠 Ready to Deploy? If you are looking for more advanced code samples, check out our collection of Generative AI Code Samples in both **Python** and **TypeScript**. ## 🗣️ Meet Other Learners, Get Support Join our official AI Discord server to meet and network with other learners taking this course and get support. ## 🚀 Building a Startup? Sign up for Microsoft for Startups Founders Hub to receive **free OpenAI credits** and up to **$150k towards Azure credits to access OpenAI models through Azure OpenAI Services**. ## 🙏 Want to help? Do you have suggestions or found spelling or code errors? Raise an issue or Create a pull request ## 📂 Each lesson includes: * A short video introduction to the topic * A written lesson located in the README * Python and TypeScript code samples supporting Azure OpenAI and OpenAI API * Links to extra resources to continue your learning ## 🗃️ Lessons | | Lesson Link | Description | Additional Learning | | :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ | | 00 | Course Setup | **Learn:** How to Setup Your Development Environment | Learn More | | 01 | Introduction to Generative AI and LLMs | **Learn:** Understanding what Generative AI is and how Large Language Models (LLMs) work. | Learn More | | 02 | Exploring and comparing different LLMs | **Learn:** How to select the right model for your use case | Learn More | | 03 | Using Generative AI Responsibly | **Learn:** How to build Generative AI Applications responsibly | Learn More | | 04 | Understanding Prompt Engineering Fundamentals | **Learn:** Hands-on Prompt Engineering Best Practices | Learn More | | 05 | Creating Advanced Prompts | **Learn:** How to apply prompt engineering techniques that improve the outcome of your prompts. | Learn More | | 06 | Building Text Generation Applications | **Build:** A text generation app using Azure OpenAI | Learn More | | 07 | Building Chat Applications | **Build:** Techniques for efficiently building and integrating chat applications. | Learn More | | 08 | Building Search Apps Vector Databases | **Build:** A search application that uses Embeddings to search for data. | Learn More | | 09 | Building Image Generation Applications | **Build:** A image generation application | Learn More | | 10 | Building Low Code AI Applications | **Build:** A Generative AI application using Low Code tools | Learn More | | 11 | Integrating External Applications with Function Calling | **Build:** What is function calling and its use cases for applications | Learn More | | 12 | Designing UX for AI Applications | **Learn:** How to apply UX design principles when developing Generative AI Applications | Learn More | | 13 | Securing Your Generative AI Applications | **Learn:** The threats and risks to AI systems and methods to secure these systems. | Learn More | | 14 | The Generative AI Application Lifecycle | **Learn:** The tools and metrics to manage the LLM Lifecycle and LLMOps | Learn More | | 15 | Retrieval Augmented Generation (RAG) and Vector Databases | **Build:** An application using a RAG Framework to retrieve embeddings from a Vector Databases | Learn More | | 16 | Open Source Models and Hugging Face | **Build:** An application using open source models available on Hugging Face | Learn More | | 17 | AI Agents | **Build:** An application using an AI Agent Framework | Learn More | | 18 | Fine-Tuning LLMs | **Learn:** The what, why and how of fine-tuning LLMs | Learn More |

ChatMemory is a simple yet powerful long-term memory manager that facilitates communication between AI and users. It organizes conversation data into history, summary, and knowledge entities, enabling quick retrieval of context and generation of clear, concise answers. The tool leverages vector search on summaries/knowledge and detailed history to provide accurate responses. It balances speed and accuracy by using lightweight retrieval and fallback detailed search mechanisms, ensuring efficient memory management and response generation beyond mere data retrieval.

Knowledge Graph Builder App is a tool designed to convert PDF documents into a structured knowledge graph stored in Neo4j. It utilizes OpenAI's GPT/Diffbot LLM to extract nodes, relationships, and properties from PDF text content. Users can upload files from local machine or S3 bucket, choose LLM model, and create a knowledge graph. The app integrates with Neo4j for easy visualization and querying of extracted information.

This starter project is designed to process `.mdx` files in the `pages` directory to use as custom context within OpenAI Text Completion prompts. It involves building a custom ChatGPT style doc search powered by Next.js, OpenAI, and Supabase. The project includes steps for pre-processing knowledge base, storing embeddings in Postgres, performing vector similarity search, and injecting content into OpenAI GPT-3 text completion prompt.

Simba is an open source, portable Knowledge Management System (KMS) designed to seamlessly integrate with any Retrieval-Augmented Generation (RAG) system. It features a modern UI and modular architecture, allowing developers to focus on building advanced AI solutions without the complexities of knowledge management. Simba offers a user-friendly interface to visualize and modify document chunks, supports various vector stores and embedding models, and simplifies knowledge management for developers. It is community-driven, extensible, and aims to enhance AI functionality by providing a seamless integration with RAG-based systems.

This repository contains code and demo for Knowledge Graph Prompting for Multi-Document Question Answering. It includes modules for data collection, training DPR and MDR models, fine-tuning T5 and LLaMA, and reproducing KGP-LLM algorithm. The workflow involves document collection, knowledge graph construction, fine-tuning models, and reproducing main table results. The repository provides instructions for environment setup, folder architecture, and running different modules.

Cognee is an open-source framework designed for creating self-improving deterministic outputs for Large Language Models (LLMs) using graphs, LLMs, and vector retrieval. It provides a platform for AI engineers to enhance their models and generate more accurate results. Users can leverage Cognee to add new information, utilize LLMs for knowledge creation, and query the system for relevant knowledge. The tool supports various LLM providers and offers flexibility in adding different data types, such as text files or directories. Cognee aims to streamline the process of working with LLMs and improving AI models for better performance and efficiency.

RAG Web UI is an intelligent dialogue system based on RAG (Retrieval-Augmented Generation) technology. It helps enterprises and individuals build intelligent Q&A systems based on their own knowledge bases. By combining document retrieval and large language models, it delivers accurate and reliable knowledge-based question-answering services. The system is designed with features like intelligent document management, advanced dialogue engine, and a robust architecture. It supports multiple document formats, async document processing, multi-turn contextual dialogue, and reference citations in conversations. The architecture includes a backend stack with Python FastAPI, MySQL + ChromaDB, MinIO, Langchain, JWT + OAuth2 for authentication, and a frontend stack with Next.js, TypeScript, Tailwind CSS, Shadcn/UI, and Vercel AI SDK for AI integration. Performance optimization includes incremental document processing, streaming responses, vector database performance tuning, and distributed task processing. The project is licensed under the Apache-2.0 License and is intended for learning and sharing RAG knowledge only, not for commercial purposes.

Neurite is an innovative project that combines chaos theory and graph theory to create a digital interface that explores hidden patterns and connections for creative thinking. It offers a unique workspace blending fractals with mind mapping techniques, allowing users to navigate the Mandelbrot set in real-time. Nodes in Neurite represent various content types like text, images, videos, code, and AI agents, enabling users to create personalized microcosms of thoughts and inspirations. The tool supports synchronized knowledge management through bi-directional synchronization between mind-mapping and text-based hyperlinking. Neurite also features FractalGPT for modular conversation with AI, local AI capabilities for multi-agent chat networks, and a Neural API for executing code and sequencing animations. The project is actively developed with plans for deeper fractal zoom, advanced control over node placement, and experimental features.

ERAG is an advanced system that combines lexical, semantic, text, and knowledge graph searches with conversation context to provide accurate and contextually relevant responses. This tool processes various document types, creates embeddings, builds knowledge graphs, and uses this information to answer user queries intelligently. It includes modules for interacting with web content, GitHub repositories, and performing exploratory data analysis using various language models.

This GPT allows to interact with the Unprotect DB to retrieve knowledge about malware evasion techniques

Expert in Tiago Forte's Second Brain methodology for digital organization.

Retrieve data on DeFi protocols and blockchains

Never lose data again. Store entire conversations for later retrieve or sharing. Do not share sensible information, data is publicly available.

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

Unlock the power of your research with the AskYourPDF Research Assistant. Bring information to your fingertips today.

I search Lambeth's planning site to provide links to policies and documents.

Download data from the internet. Fetch the content of sites and make it available to the session, given a URL.

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

Efficient Assistant for task management, info retrieval, and scheduling. Offers dynamic, personalized support while ensuring user privacy and data security. Ideal for organizing tasks, setting reminders, and providing up-to-date information.

I browse docs to answer Svelte & Supabase queries.

Can't quite remember that thought you had? Use this GPT to help guide you back to your memory.

Finds and provides RSS feed URLs for given website links.

Expert at web navigation and information retrieval.

Write what you'd like researched. Get information in a table format.

Golden Retriever training expert providing advice and tips

Retrieves hunting-related data for each state. Providing insightful data analysis on trends in hunting statistics. (beta)

Comprehensive training and wellness guide for Chesapeake Bay Retrievers.