Best AI tools for< Find Knowledge Bases >

RAG ChatBot is a service that allows users to easily train and share chatbots. It can transform PDFs, URLs, and text into smart chatbots that can be embedded anywhere with an iframe. RAG ChatBot is designed to make knowledge sharing easier and more efficient. It offers a variety of features to help users create and manage their chatbots, including easy knowledge training, continuous improvement, seamless integration with OpenAI Custom GPTs, secure API key integration, continuous optimization, and online privacy control.

Wikidata is a free and open knowledge base that can be read and edited by both humans and machines. It acts as central storage for the structured data of its Wikimedia sister projects including Wikipedia, Wikivoyage, Wiktionary, Wikisource, and others. Wikidata also provides support to many other sites and services beyond just Wikimedia projects!

Document360 is an AI-powered knowledge base software that helps businesses create, manage, and share documentation. It offers a range of features to make documentation easier and more efficient, including a user-friendly interface, advanced search capabilities, rich analytics, and AI-powered suggestions. Document360 can be used by businesses of all sizes to improve their customer service, product documentation, and internal knowledge sharing.

RquestR is an AI-powered knowledge management platform designed specifically for procurement professionals. It streamlines projects, enables instant answers retrieval, and facilitates informed decision-making. The platform offers features such as intelligent document querying, automated Q&A generation, and knowledge base building. RquestR helps in reducing response time by up to 40% and enhancing decision-making accuracy by 30%. It provides a centralized knowledge hub for managing RFPs, security questionnaires, and Q&As, all while ensuring enterprise-grade security. The platform revolutionizes the procurement process by leveraging advanced AI for lightning-fast information retrieval, accurate responses, and adaptive learning.

Nouswise is an AI-powered personal search engine that provides trusted answers from your sources, saving you up to 4 hours a week. It allows you to upload and explore books, validate answers, and create a personal knowledge base. The application is grounded in the personal information you trust the most, offering a unique experience with verifiable information and context awareness. Nouswise aims to make everything searchable and ensures privacy and security beyond the limit.

Intercom is a customer engagement platform that helps businesses build better relationships with their customers through personalized messaging, automated support, and self-service help. Intercom's knowledge base software is a powerful tool that allows businesses to create and manage a comprehensive knowledge base that can help customers find answers to their questions quickly and easily. With Intercom's knowledge base software, businesses can reduce support volume, increase efficiency, and deliver personalized support at scale.

Recall is a web and mobile application that allows users to summarize and save any online content. It uses artificial intelligence to automatically categorize and connect saved content, making it easy to find and rediscover later. Recall also offers spaced repetition learning, data export, and offline access.

Datagrid is an AI-powered platform that acts as your co-worker, helping you find, enrich, and delegate information. It harnesses the power of AI to enrich datasets, access knowledge, execute tasks, and automate follow-ups. Datagrid AI Agents can free your team from the burden of enriching messy data, allowing them to focus on revenue-generating tasks. The platform offers features like AI enrichment, data processing, long-form content writing, generating insights, and creating a knowledge base.

ThreadScribe.ai is a chatbot for Slack that uses cutting-edge AI to transform your Slack conversations into a structured, easily searchable knowledge base. Effortlessly organize your Slack discussions into searchable knowledge with one click. It utilizes cutting-edge AI to summarize lengthy discussions into concise, actionable insights, saving you time and enhancing decision-making. ThreadScribe.ai integrates effortlessly with Slack, ensuring a smooth transition from casual conversations to structured knowledge without disrupting your workflow. It transforms the maze of Slack channels into a navigable treasure trove of knowledge, helping you find the signal through the noise.

Brainfish is an AI-powered customer support tool that helps businesses provide self-service support to their customers. It uses advanced AI to help customers find answers to their questions quickly and easily, reducing the need for human support. Brainfish also provides businesses with insights into customer concerns, helping them improve their knowledge base content and provide better support.

Gameguide.ai is the first-ever AI-powered game guide that offers personalized and instant gaming guidance to players. It provides tips, strategies, walkthroughs, and real-time answers to gaming-related queries. The platform aims to create a community-driven knowledge base where gamers can contribute and enhance the accuracy of the AI's responses. Gameguide.ai also focuses on building a gaming community by offering game-specific features like popular questions, influencer profiles, interactive polls, and collaborative challenges.

Brain Assistant is an AI-driven personal assistant that provides real-time, AI-powered internet searches and the ability to create a knowledge base from your own documents and web pages. It offers optimized search results, personalized 'brain' creation, multilingual support, and prioritizes user privacy by avoiding ads and data collection. Users can ask a wide range of questions and receive tailored results based on their specific needs.

Instabase is an AI-native unstructured data platform that helps businesses transform their processes stuck in unstructured data. It offers solutions for automating document processing workflows, analyzing data from any document or knowledge base, and surfacing insights across all company data. Instabase leverages generative AI, agentic reasoning, and federated processing to enable users to automate processes, find information, and make smarter decisions faster. The platform prioritizes AI privacy, security, and trust, providing users with complete control over their data and enterprise-grade security measures. Instabase has received several awards and recognitions for its innovative approach to leveraging AI for business solutions.

Leena AI is a Gen AI employee assistant that reduces IT, HR, Finance tickets. It guarantees a 70% self-service ratio in the contract. Leena AI centralizes knowledge that is scattered across the enterprise, making information easy to find right on chat with a simple query. The knowledge is auto-updated when changes are made, so your employees always get support that is both relevant and accurate. Leena AI integrates with all knowledge base systems within your enterprise from day one, eliminating the need for any consolidation or migration effort across the knowledge base systems. The work assistant tailors responses to employee queries based on their role, team and access level which boosts employee experience while adhering to security protocols and preventing unauthorized access to information. Leena AI analyzes historically closed tickets and learns from their resolutions to create knowledge articles that can prevent similar tickets from being raised again. Leena AI breaks down large policy documents and knowledge articles into consumable snippets so the responses are sharper and more specific to the employee’s query.

Open Knowledge Maps is the world's largest AI-based search engine for scientific knowledge. It aims to revolutionize discovery by increasing the visibility of research findings for science and society. The platform is open and nonprofit, based on the principles of open science, with a mission to create an inclusive, sustainable, and equitable infrastructure for all users. Users can map research topics with AI, find documents, and identify concepts to enhance their literature search experience.

FashionAdvisor.AI is an AI tool designed to help users with fashion-related queries and outfit combinations. Users can ask questions about what to wear with specific clothing items or colors and receive personalized advice and suggestions. The tool leverages artificial intelligence to provide tailored fashion recommendations based on current trends and style preferences. With a vast database of fashion knowledge, FashionAdvisor.AI aims to assist users in creating stylish and cohesive outfits for various occasions.

Collato is an AI assistant designed to help product teams save time on writing documents, answering questions, and generating new content. It can find, summarize, and generate new content based on your own product knowledge, saving you hours in manual work. Collato is also self-hosted, so you can keep your data private and secure.

PGH.AI is an AI community hub based in Pittsburgh, offering a platform for individuals interested in artificial intelligence to connect, collaborate, and learn. The website serves as a nexus for professionals, enthusiasts, and learners to engage in discussions, share resources, and seek opportunities within the AI field. With a focus on fostering a supportive and inclusive environment, PGH.AI aims to facilitate networking, knowledge-sharing, and skill development among its members.

LuxAuraAI is an AI-powered platform that helps users discover their perfect skincare routine through a personalized quiz. By leveraging expert knowledge and science-backed results, LuxAuraAI provides tailored skincare recommendations based on individual skin needs. The platform aims to simplify the process of finding suitable skincare products by incorporating insights from dermatologists and skincare experts. LuxAuraAI is designed to offer a convenient and effective solution for those seeking a skincare regimen that is both personalized and backed by scientific research.

MiMi is a website intelligence tool that uses AI to enhance the user experience and drive sales. It offers a range of features including semantic search, chatbot, recommendations, virtual assistant, dynamic pricing, and automation. MiMi's AI engine can automatically learn and update knowledge from your site to provide an AI chatbot that can answer questions from visitors automatically. The machine learning algorithms can also learn from your site products and visitor behavior to bring recommender systems for your site. MiMi's AI algorithm serves as a virtual sales assistant, assisting websites in making flexible and tailored pricing decisions for each customer based on their behavior.

Awesome AI GPTs is an open repository that collects resources and fun ways to use OpenAI GPTs. It includes databases, search tools, open-source projects, articles, attack and defense strategies, installation of custom plugins, knowledge bases, and community interactions related to GPTs. Users can find curated lists, leaked prompts, and various GPT applications in this repository. The project aims to empower users with AI capabilities and foster collaboration in the AI community.

Knowledge Conflicts for LLMs: A Survey is a repository containing a survey paper that investigates three types of knowledge conflicts: context-memory conflict, inter-context conflict, and intra-memory conflict within Large Language Models (LLMs). The survey reviews the causes, behaviors, and possible solutions to these conflicts, providing a comprehensive analysis of the literature in this area. The repository includes detailed information on the types of conflicts, their causes, behavior analysis, and mitigating solutions, offering insights into how conflicting knowledge affects LLMs and how to address these conflicts.

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.

ChatLaw is an open-source legal large language model tailored for Chinese legal scenarios. It aims to combine LLM and knowledge bases to provide solutions for legal scenarios. The models include ChatLaw-13B and ChatLaw-33B, trained on various legal texts to construct dialogue data. The project focuses on improving logical reasoning abilities and plans to train models with parameters exceeding 30B for better performance. The dataset consists of forum posts, news, legal texts, judicial interpretations, legal consultations, exam questions, and court judgments, cleaned and enhanced to create dialogue data. The tool is designed to assist in legal tasks requiring complex logical reasoning, with a focus on accuracy and reliability.

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.

The UltraRAG framework is a researcher and developer-friendly RAG system solution that simplifies the process from data construction to model fine-tuning in domain adaptation. It introduces an automated knowledge adaptation technology system, supporting no-code programming, one-click synthesis and fine-tuning, multidimensional evaluation, and research-friendly exploration work integration. The architecture consists of Frontend, Service, and Backend components, offering flexibility in customization and optimization. Performance evaluation in the legal field shows improved results compared to VanillaRAG, with specific metrics provided. The repository is licensed under Apache-2.0 and encourages citation for support.

Taiyi (太一) is a bilingual large language model fine-tuned for diverse biomedical tasks. It aims to facilitate communication between healthcare professionals and patients, provide medical information, and assist in diagnosis, biomedical knowledge discovery, drug development, and personalized healthcare solutions. The model is based on the Qwen-7B-base model and has been fine-tuned using rich bilingual instruction data. It covers tasks such as question answering, biomedical dialogue, medical report generation, biomedical information extraction, machine translation, title generation, text classification, and text semantic similarity. The project also provides standardized data formats, model training details, model inference guidelines, and overall performance metrics across various BioNLP tasks.

Bedrock Engineer is an autonomous software development agent application that utilizes Amazon Bedrock. It allows users to customize, create/edit files, execute commands, search the web, use a knowledge base, utilize multi-agents, generate images, and more. The tool provides an interactive chat interface with AI agents, file system operations, web search capabilities, project structure management, code analysis, code generation, data analysis, agent and tool customization, chat history management, and multi-language support. Users can select and customize agents, choose from various tools like file system operations, web search, Amazon Bedrock integration, and system command execution. Additionally, the tool offers features for website generation, connecting to design system data sources, AWS Step Functions ASL definition generation, diagram creation using natural language descriptions, and multi-language support.

Txtai is an all-in-one embeddings database for semantic search, LLM orchestration, and language model workflows. It combines vector indexes, graph networks, and relational databases to enable vector search with SQL, topic modeling, retrieval augmented generation, and more. Txtai can stand alone or serve as a knowledge source for large language models (LLMs). Key features include vector search with SQL, object storage, topic modeling, graph analysis, multimodal indexing, embedding creation for various data types, pipelines powered by language models, workflows to connect pipelines, and support for Python, JavaScript, Java, Rust, and Go. Txtai is open-source under the Apache 2.0 license.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

Just-Chat is a containerized application that allows users to easily set up and chat with their AI agent. Users can customize their AI assistant using a YAML file, add new capabilities with Python tools, and interact with the agent through a chat web interface. The tool supports various modern models like DeepSeek Reasoner, ChatGPT, LLAMA3.3, etc. Users can also use semantic search capabilities with MeiliSearch to find and reference relevant information based on meaning. Just-Chat requires Docker or Podman for operation and provides detailed installation instructions for both Linux and Windows users.

MindsDB is a platform for customizing AI from enterprise data. You can create, serve, and fine-tune models in real-time from your database, vector store, and application data. MindsDB "enhances" SQL syntax with AI capabilities to make it accessible for developers worldwide. With MindsDB’s nearly 200 integrations, any developer can create AI customized for their purpose, faster and more securely. Their AI systems will constantly improve themselves — using companies’ own data, in real-time.

EasyEdit is a Python package for edit Large Language Models (LLM) like `GPT-J`, `Llama`, `GPT-NEO`, `GPT2`, `T5`(support models from **1B** to **65B**), the objective of which is to alter the behavior of LLMs efficiently within a specific domain without negatively impacting performance across other inputs. It is designed to be easy to use and easy to extend.

Shandu is an advanced AI research system that automates comprehensive research processes using language models, web scraping, and iterative exploration to generate well-structured reports with citations. It features intelligent state-based workflow, deep exploration, multi-source information synthesis, enhanced web scraping, smart source evaluation, content analysis pipeline, comprehensive report generation, parallel processing, adaptive search strategy, and full citation management.

This repository is dedicated to collecting and categorizing papers related to Retrieval-Augmented Generation (RAG) for AI-generated content. It serves as a survey repository based on the paper 'Retrieval-Augmented Generation for AI-Generated Content: A Survey'. The repository is continuously updated to keep up with the rapid growth in the field of RAG.

Khoj is an open-source, personal AI assistant that extends your capabilities by creating always-available AI agents. You can share your notes and documents to extend your digital brain, and your AI agents have access to the internet, allowing you to incorporate real-time information. Khoj is accessible on Desktop, Emacs, Obsidian, Web, and Whatsapp, and you can share PDF, markdown, org-mode, notion files, and GitHub repositories. You'll get fast, accurate semantic search on top of your docs, and your agents can create deeply personal images and understand your speech. Khoj is self-hostable and always will be.

chromem-go is an embeddable vector database for Go with a Chroma-like interface and zero third-party dependencies. It enables retrieval augmented generation (RAG) and similar embeddings-based features in Go apps without the need for a separate database. The focus is on simplicity and performance for common use cases, allowing querying of documents with minimal memory allocations. The project is in beta and may introduce breaking changes before v1.0.0.

The Amazon Transcribe Live Call Analytics (LCA) with Agent Assist Sample Solution is designed to help contact centers assess and optimize caller experiences in real time. It leverages Amazon machine learning services like Amazon Transcribe, Amazon Comprehend, and Amazon SageMaker to transcribe and extract insights from contact center audio. The solution provides real-time supervisor and agent assist features, integrates with existing contact centers, and offers a scalable, cost-effective approach to improve customer interactions. The end-to-end architecture includes features like live call transcription, call summarization, AI-powered agent assistance, and real-time analytics. The solution is event-driven, ensuring low latency and seamless processing flow from ingested speech to live webpage updates.

Well-Architected Infrastructure as Code (IaC) Analyzer is a project demonstrating how generative AI can evaluate infrastructure code for alignment with best practices. It features a modern web application allowing users to upload IaC documents, complete IaC projects, or architecture diagrams for assessment. The tool provides insights into infrastructure code alignment with AWS best practices, offers suggestions for improving cloud architecture designs, and can generate IaC templates from architecture diagrams. Users can analyze CloudFormation, Terraform, or AWS CDK templates, architecture diagrams in PNG or JPEG format, and complete IaC projects with supporting documents. Real-time analysis against Well-Architected best practices, integration with AWS Well-Architected Tool, and export of analysis results and recommendations are included.

This repository contains a comprehensive collection of 63 must-know Large Language Models (LLMs) interview questions. It covers topics such as the architecture of LLMs, transformer models, attention mechanisms, training processes, encoder-decoder frameworks, differences between LLMs and traditional statistical language models, handling context and long-term dependencies, transformers for parallelization, applications of LLMs, sentiment analysis, language translation, conversation AI, chatbots, and more. The readme provides detailed explanations, code examples, and insights into utilizing LLMs for various tasks.

Expert in sourcing and organizing knowledge databases for GPTs.

Documentation for Knowledge Base

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