Best AI tools for< Research Data >

Roundtable is an AI-assisted data cleaning tool that helps improve market research data quality by efficiently analyzing and cleaning survey data. It offers an easy-to-integrate API for cleaning open-ended survey responses, saving users up to 70% of their time. The tool is trusted by leaders in over 25 global markets and provides real-time behavioral tracking, multilingual functionality, and dynamic clustering to enhance data quality and accuracy.

Marvin is an AI research software that serves as the perfect AI research assistant for qualitative research. It automates tedious parts of qualitative research, allowing users to analyze hours of research in minutes. Marvin helps in centralizing, searching, and sharing user research data, making it easily accessible for the whole team. With AI-powered enhancements, Marvin assists in consolidating user insights, finding patterns, and backing decisions with evidence. The tool streamlines the research journey by managing user interview panels, recruiting participants effectively, and providing features like automatic transcripts, video clips, and privacy filters for compliance. Marvin offers different pricing plans suitable for small teams, startups, companies with multiple teams, and large organizations.

Looppanel is an AI-powered research assistant that revolutionizes the way research data is managed. It automatically records calls, transcribes them, and centralizes all research data in one place. Looppanel's highly accurate transcripts support multiple languages and accents, enabling users to focus on interviews while AI takes notes. The platform simplifies analysis, allows for time-stamped note-taking, and facilitates collaboration among team members. Looppanel ensures data security and compliance with high standards, making it a valuable tool for researchers and professionals.

ScholarAI is an AI-powered scientific research tool that offers a wide range of features to help users navigate and extract insights from scientific literature. With access to over 200 million peer-reviewed articles, ScholarAI allows users to conduct abstract searches, literature mapping, PDF reading, literature reviews, gap analysis, direct Q&A, table and figure extraction, citation management, and project management. The tool is designed to accelerate the research process and provide tailored scientific insights to users.

Elsevier is an information analytics business that supports researchers and healthcare professionals in advancing science and improving healthcare outcomes. They provide high-quality data and analytics to help researchers, librarians, and research leaders address challenges at every stage of the research journey. Elsevier offers researcher tools, research management solutions, and evaluation services to enhance productivity and research impact.

Notably is a research synthesis platform that uses AI to help researchers analyze and interpret data faster. It offers a variety of features, including a research repository, AI research, digital sticky notes, video transcription, and cluster analysis. Notably is used by companies and organizations of all sizes to conduct product research, market research, academic research, and more.

Avidnote is an AI tool designed for research writing, reading, and analysis. It enables users to write or read research papers faster, analyze research data with AI templates, summarize text, find research gaps, transcribe interviews, and more. Avidnote offers AI functionalities tailored for researchers, recommended by universities, and supported by researchers worldwide. The platform provides free and paid plans with varying features and benefits to cater to different user needs.

Looppanel is a user research analysis and repository tool that uses AI to help researchers save time and improve the quality of their work. It offers a range of features, including automated transcription, AI note-taking, video snipping, and advanced search capabilities. Looppanel is designed to make it easy for researchers to capture, organize, and analyze their research data, so they can focus on what matters most: uncovering insights and making better decisions.

Perceive Now is the world's first Large Language Model fine-tuned with IP and Market Research data. It offers custom IP and Market reports for various industries, providing detailed insights and analysis to support decision-making processes. The platform helps in identifying market trends, conducting due diligence, managing deal flow, and maximizing IP and licensing opportunities. Perceive Now is a game-changer in prior art search, increasing the odds of patent grant success. It has significantly reduced research costs and time, accessing over 100M IP and market data sources and assisting in securing funding worth $500M.

Pvalyou is an AI application designed to enhance productivity by providing AI agents that offer unparalleled research capabilities, reliability, personalization, and cross-interface functionality. The platform features Val, a sophisticated AI analyst, and a coordinated system of multiple sub-agents to distribute complexity and computation efficiently. Pvalyou aims to revolutionize organizational AI analysts by offering a deeply personalized and intuitive experience for users.

Dimensions AI is an advanced scientific research database that provides a suite of research applications and time-saving solutions for intelligent discovery and faster insight. It hosts the largest collection of interconnected global research data, including publications, clinical trials, patents, policy documents, grants, datasets, and online citations. The platform offers easy-to-understand visualizations, purpose-built applications, and integrated AI technology to speed up research interpretation and analysis. Dimensions is designed to propel research by connecting the dots across the research ecosystem and saving researchers hours of time.

JADBio is an automated machine learning (AutoML) platform designed to accelerate biomarker discovery and drug development processes. It offers a no-code solution that automates the discovery of biomarkers and interprets their role based on research needs. JADBio can parse multi-omics data, including genomics, transcriptome, metagenome, proteome, metabolome, phenotype/clinical data, and images, enabling users to efficiently discover insights for various conditions such as cancer, immune system disorders, chronic diseases, infectious diseases, and mental health.

TOPBOTS is a platform focused on Applied AI for Business, providing insights and resources on artificial intelligence, machine learning, automation, bots, and chatbots. The website covers a wide range of topics such as computer vision, conversational AI, natural language processing, HR & recruiting, marketing, and research summaries. TOPBOTS aims to help businesses understand and apply technical breakthroughs in AI to enhance their operations and strategies.

FetchFox is an AI-powered web scraping tool that allows users to extract data from any website by providing a prompt in plain English. It runs as a Chrome Extension and can bypass anti-scraping measures on sites like LinkedIn and Facebook. FetchFox is designed to quickly gather data for tasks such as lead generation, research data assembly, and market segment analysis.

Wolters Kluwer is a global provider of professional information, software solutions, and services for various industries, including healthcare, tax and accounting, ESG, finance, compliance, and legal. The company's solutions combine domain expertise with advanced technology to help professionals make informed decisions, optimize processes, and achieve better outcomes. Wolters Kluwer's offerings include clinical decision support tools, tax and accounting software, ESG reporting solutions, regulatory compliance solutions, and legal research databases.

The Human Years to Dog Years Calculator is a fun and professional tool that accurately converts human age to dog years based on AI and scientific research. It considers breed-specific characteristics to provide precise age comparisons, continuously updated with the latest research data. Users can select their birth date and dog breed to discover their equivalent age in the dog world, gaining insights into different life stages and growth patterns across breeds.

Lime is an AI-powered data research assistant designed to streamline and enhance the data research process. It leverages artificial intelligence to assist users in gathering, analyzing, and interpreting data efficiently and accurately. Lime aims to simplify complex data research tasks and provide valuable insights to users, ultimately saving time and improving decision-making processes.

DMLR (Data-centric Machine Learning Research) is an AI tool that focuses on advancing research in data-centric machine learning. It organizes workshops, research retreats, maintains a journal, and runs a working group to support infrastructure projects. The platform covers topics such as data collection, governance, bias, and drifts, as well as data-centric explainable AI and AI alignment. DMLR encourages submissions around the theme of AI for Science, using AI to tackle scientific challenges and accelerate discoveries.

Maya is an AI-powered data robot that provides personalized answers and insights for enterprise data research. It combines multiple data sources and tools into one, automates tasks, offers smart suggestions, and saves time. Maya understands the specific insights required for each workflow and provides justification for implementation. It can access data from various sources, including internal integrations and external sources, and can translate queries in up to 14 languages. Maya is constantly learning and improving through advanced machine learning and regular updates with new data. It prioritizes data privacy and security, following industry-standard protocols to keep customer data safe.

Papertalk.io is an AI-powered platform that revolutionizes research by providing users with access to over 215 million papers, AI-generated explanations, and actionable insights. The platform offers precision search tools, AI-powered understanding of research papers, and personalized guidance on applying insights practically. Papertalk.io aims to make research more accessible and approachable for users from diverse backgrounds, transforming complex data into easy-to-digest formats to foster innovation and expertise.

This repository serves as a comprehensive survey on the application of Large Language Models (LLMs) on tabular data, focusing on tasks such as prediction, data generation, and table understanding. It aims to consolidate recent progress in this field by summarizing key techniques, metrics, datasets, models, and optimization approaches. The survey identifies strengths, limitations, unexplored territories, and gaps in the existing literature, providing insights for future research directions. It also offers code and dataset references to empower readers with the necessary tools and knowledge to address challenges in this rapidly evolving domain.

AI Audio Datasets List (AI-ADL) is a comprehensive collection of datasets consisting of speech, music, and sound effects, used for Generative AI, AIGC, AI model training, and audio applications. It includes datasets for speech recognition, speech synthesis, music information retrieval, music generation, audio processing, sound synthesis, and more. The repository provides a curated list of diverse datasets suitable for various AI audio tasks.

Scientific Large Language Models (Sci-LLMs) is a repository that collects papers on scientific large language models, focusing on biology and chemistry domains. It includes textual, molecular, protein, and genomic languages, as well as multimodal language. The repository covers various large language models for tasks such as molecule property prediction, interaction prediction, protein sequence representation, protein sequence generation/design, DNA-protein interaction prediction, and RNA prediction. It also provides datasets and benchmarks for evaluating these models. The repository aims to facilitate research and development in the field of scientific language modeling.

This repository is a curated list of awesome public object detection and recognition datasets. It includes a wide range of datasets related to object detection and recognition tasks, such as general detection and recognition datasets, autonomous driving datasets, adverse weather datasets, person detection datasets, anti-UAV datasets, optical aerial imagery datasets, low-light image datasets, infrared image datasets, SAR image datasets, multispectral image datasets, 3D object detection datasets, vehicle-to-everything field datasets, super-resolution field datasets, and face detection and recognition datasets. The repository also provides information on tools for data annotation, data augmentation, and data management related to object detection tasks.

The 'awesome-sound_event_detection' repository is a curated reading list focusing on sound event detection and Sound AI. It includes research papers covering various sub-areas such as learning formulation, network architecture, pooling functions, missing or noisy audio, data augmentation, representation learning, multi-task learning, few-shot learning, zero-shot learning, knowledge transfer, polyphonic sound event detection, loss functions, audio and visual tasks, audio captioning, audio retrieval, audio generation, and more. The repository provides a comprehensive collection of papers, datasets, and resources related to sound event detection and Sound AI, making it a valuable reference for researchers and practitioners in the field.

Palera1n-Jailbreak is a comprehensive guide and tool for jailbreaking iOS 17.6.1 to iOS 15 and iPadOS 18.1 beta 4, 17. It provides information on compatibility, installation, achievements, research data, and working tweak list. The tool is based on the checkm8 exploit, allowing customization of iOS devices with third-party apps and tweaks. Palera1n offers features like root access, tweak injection, and custom themes, making it a valuable tool for iOS customization enthusiasts.

AiiDA (www.aiida.net) is a workflow manager for computational science with a strong focus on provenance, performance and extensibility. **Features** * **Workflows:** Write complex, auto-documenting workflows in python, linked to arbitrary executables on local and remote computers. The event-based workflow engine supports tens of thousands of processes per hour with full checkpointing. * **Data provenance:** Automatically track inputs, outputs & metadata of all calculations in a provenance graph for full reproducibility. Perform fast queries on graphs containing millions of nodes. * **HPC interface:** Move your calculations to a different computer by changing one line of code. AiiDA is compatible with schedulers like SLURM, PBS Pro, torque, SGE or LSF out of the box. * **Plugin interface:** Extend AiiDA with plugins for new simulation codes (input generation & parsing), data types, schedulers, transport modes and more. * **Open Science:** Export subsets of your provenance graph and share them with peers or make them available online for everyone on the Materials Cloud. * **Open source:** AiiDA is released under the MIT open source license

Awesome LLM compression research papers and tools to accelerate LLM training and inference.

Awesome-LLMs-for-Video-Understanding is a repository dedicated to exploring Video Understanding with Large Language Models. It provides a comprehensive survey of the field, covering models, pretraining, instruction tuning, and hybrid methods. The repository also includes information on tasks, datasets, and benchmarks related to video understanding. Contributors are encouraged to add new papers, projects, and materials to enhance the repository.

Awesome-Graph-LLM is a curated collection of research papers exploring the intersection of graph-based techniques with Large Language Models (LLMs). The repository aims to bridge the gap between LLMs and graph structures prevalent in real-world applications by providing a comprehensive list of papers covering various aspects of graph reasoning, node classification, graph classification/regression, knowledge graphs, multimodal models, applications, and tools. It serves as a valuable resource for researchers and practitioners interested in leveraging LLMs for graph-related tasks.

llm_benchmarks is a collection of benchmarks and datasets for evaluating Large Language Models (LLMs). It includes various tasks and datasets to assess LLMs' knowledge, reasoning, language understanding, and conversational abilities. The repository aims to provide comprehensive evaluation resources for LLMs across different domains and applications, such as education, healthcare, content moderation, coding, and conversational AI. Researchers and developers can leverage these benchmarks to test and improve the performance of LLMs in various real-world scenarios.

Paper-Reading-ConvAI is a repository that contains a list of papers, datasets, and resources related to Conversational AI, mainly encompassing dialogue systems and natural language generation. This repository is constantly updating.

A curated list of awesome Model Context Protocol (MCP) servers that enable AI models to securely interact with local and remote resources through standardized server implementations. The list focuses on production-ready and experimental servers extending AI capabilities through file access, database connections, API integrations, and other contextual services.

This repository is a curated list of awesome large AI models in audio signal processing, focusing on the application of large language models to audio tasks. It includes survey papers, popular large audio models, automatic speech recognition, neural speech synthesis, speech translation, other speech applications, large audio models in music, and audio datasets. The repository aims to provide a comprehensive overview of recent advancements and challenges in applying large language models to audio signal processing, showcasing the efficacy of transformer-based architectures in various audio tasks.

ScreenAgent is a project focused on creating an environment for Visual Language Model agents (VLM Agent) to interact with real computer screens. The project includes designing an automatic control process for agents to interact with the environment and complete multi-step tasks. It also involves building the ScreenAgent dataset, which collects screenshots and action sequences for various daily computer tasks. The project provides a controller client code, configuration files, and model training code to enable users to control a desktop with a large model.

SEED-Bench is a comprehensive benchmark for evaluating the performance of multimodal large language models (LLMs) on a wide range of tasks that require both text and image understanding. It consists of two versions: SEED-Bench-1 and SEED-Bench-2. SEED-Bench-1 focuses on evaluating the spatial and temporal understanding of LLMs, while SEED-Bench-2 extends the evaluation to include text and image generation tasks. Both versions of SEED-Bench provide a diverse set of tasks that cover different aspects of multimodal understanding, making it a valuable tool for researchers and practitioners working on LLMs.

The LLMEvaluation repository is a comprehensive compendium of evaluation methods for Large Language Models (LLMs) and LLM-based systems. It aims to assist academics and industry professionals in creating effective evaluation suites tailored to their specific needs by reviewing industry practices for assessing LLMs and their applications. The repository covers a wide range of evaluation techniques, benchmarks, and studies related to LLMs, including areas such as embeddings, question answering, multi-turn dialogues, reasoning, multi-lingual tasks, ethical AI, biases, safe AI, code generation, summarization, software performance, agent LLM architectures, long text generation, graph understanding, and various unclassified tasks. It also includes evaluations for LLM systems in conversational systems, copilots, search and recommendation engines, task utility, and verticals like healthcare, law, science, financial, and others. The repository provides a wealth of resources for evaluating and understanding the capabilities of LLMs in different domains.

This repository serves as a practical guide for Medical Large Language Models (Medical LLMs) and provides resources, surveys, and tools for building, fine-tuning, and utilizing LLMs in the medical domain. It covers a wide range of topics including pre-training, fine-tuning, downstream biomedical tasks, clinical applications, challenges, future directions, and more. The repository aims to provide insights into the opportunities and challenges of LLMs in medicine and serve as a practical resource for constructing effective medical LLMs.

Your AI research assistant, for turning a problem into a research, developing research questions, generating plans, analyzing data and improving research workflows for project success

A UI/UX assistant for design principles, UX research, analyzing research data, and UI layout generation.

Guides scientific investigations and theoretical research methodologies.

Assists in psychological meta-analysis research with R language expertise.

a robot scholar reviewing social science research

Clean and structure your raw data with automatic file output for your Custom GPT knowledge.

Helps you write market research briefs and survey questions.

Expert in scientific research grants, answers in Japanese with detailed references and citations.

Find recent research for your area of biological interest.

당신의 레포트 작성을 위한 조력자. 레포트 작성, 레포트 수정, 자료 조사까지 모든 단계를 지원합니다.

CYO KATSUI

Sports betting arbitrage assistant for horse racing and other sports.

Expert math tutor and problem solver with online research and data analysis skills.

Your go-to film data guru

Hi ;) Ask me for data & insights gathered from an environmentally aware global community

Your go-to source for in-depth US zip code demographics and statistics, with easy-to-download data tables.

Finance fact-checker with accuracy scoring, using sources like NerdWallet, Investopedia, BEA, and St. Louis Fed.

MTG info and URL crafter

암호화폐 시장 분석 및 예측

Average score from Metacritic, Rotten Tomatoes, IMDB, TMDB for any movie or series.