Best AI tools for< Design Research Studies >

RealEye is an online research platform that uses webcam eye-tracking to collect data on user behavior. It allows researchers to conduct studies on attention, emotions, and mouse/key tracking. RealEye is easy to use and does not require any special equipment or software. It is a valuable tool for researchers who want to gain insights into how users interact with websites and other online content.

Maze is a continuous product discovery platform that enables users to enrich product decisions with intuitive user research. It offers a wide range of features such as prototype testing, website testing, surveys, interview studies, and more. With AI-powered tools and integrations with popular design tools, Maze helps users scale user insights and speed up product launches. The platform provides Enterprise-level protection, encrypted transmission, access control, data center security, GDPR compliance, SSO, and private workspaces to ensure data security and compliance. Trusted by companies of all industries and sizes, Maze empowers teams to make user-informed decisions and drive faster product iteration for a better user experience.

GuidedTrack is a versatile platform that allows users to create apps, surveys, educational modules, studies, tools, and prototypes without the need to hire a programmer. It caters to various user groups such as agencies, marketers, researchers, educators, entrepreneurs, and anyone with an idea. The platform offers a range of features including advanced interactive study design, adaptive lessons creation, rapid prototype development, and more. GuidedTrack is praised for its user-friendly interface, flexibility, efficiency, and excellent customer support.

Ludo.ai is a comprehensive AI-powered platform designed to assist game studios in the pre-production stage of game development. It offers a suite of tools that leverage AI text generation, AI image generation, and AI-powered semantic search to streamline the process of researching, generating, and developing game concepts. Ludo.ai empowers game developers with the ability to generate new game ideas, monitor market trends, conduct in-depth research, organize and boost productivity, and access a range of resources to enhance their game design process.

Moxie is an AI-powered academic research writing companion that assists users in refining arguments, guiding research, and enhancing academic voice. It offers personalized feedback, AI-powered writing assistance, and tools for research design. Unlike AI content generators, Moxie empowers scholars to tackle complex tasks while preserving their critical thinking. The platform provides premium AI models, interactive learning sessions, and a personalized approach to academic writing. Users can streamline research processes, refine arguments, and receive actionable feedback to enhance their academic work.

The Institute for Protein Design is a research institute at the University of Washington that uses computational design to create new proteins that solve modern challenges in medicine, technology, and sustainability. The institute's research focuses on developing new protein therapeutics, vaccines, drug delivery systems, biological devices, self-assembling nanomaterials, and bioactive peptides. The institute also has a strong commitment to responsible AI development and has developed a set of principles to guide its use of AI in research.

ODDY is a research copilot for UX design that conducts desk research and design reviews in seconds. It provides actionable insights, best practices, and direct references to help UX designers transform their challenges into better designs.

MIT Sloan Teaching & Learning Technologies connects MIT Sloan to research-driven best practices, resources, and training in instructional technology and design. They help the community make an impact in the classroom and beyond. They offer various services such as trainings, practice sessions, how-to guides, consultations, and a teaching studio. Their latest news and announcements include supporting learning with AI-generated images, providing students with access to Microsoft Copilot, and making Microsoft Copilot available for faculty and staff.

UXSquid is a comprehensive UX research software platform and tool that guides users through the user research process with interview question examples, plans, templates, and a cheat sheet. It offers a free trial, requires no credit card, and allows users to cancel anytime. UXSquid's platform makes it easy to conduct user interviews and gather feedback. Users can use its automation tools to set up interviews with their target audience and gather valuable information. UXSquid analyzes user experiences and interactions with a company using cutting-edge artificial intelligence. It then makes important suggestions and enhancements to improve a product for its users.

Archistar is a leading property research platform that utilizes data and AI to help investors, developers, architects, and government officials make confident and compliant decisions. The platform offers features such as finding the best use of a site, researching real estate rules and risks, generating 3D design concepts with AI, and fast-tracking building permit assessments. With over 100,000 users, Archistar provides access to advanced algorithms, filters, and market insights to discover real estate opportunities efficiently.

User Evaluation is an AI-first user research platform that leverages AI technology to provide instant insights, comprehensive reports, and on-demand answers to enhance customer research. The platform offers features such as AI-driven data analysis, multilingual transcription, live timestamped notes, AI reports & presentations, and multimodal AI chat. User Evaluation empowers users to analyze qualitative and quantitative data, synthesize AI-generated recommendations, and ensure data security through encryption protocols. It is designed for design agencies, product managers, founders, and leaders seeking to accelerate innovation and shape exceptional product experiences.

Victor Dibia's website showcases his expertise in Applied Machine Learning and Human-Computer Interaction (HCI). He is a Principal Research Software Engineer at Microsoft Research, focusing on Generative AI. The site features his publications, projects, CV, and blog posts, covering topics such as multi-agent systems, recommender systems, and more. Victor's work has been recognized in conferences and media outlets, highlighting his contributions to the field of AI and HCI.

MindCopilot is an AI tool designed to enhance the user experience of ChatGPT by providing a better UI. It offers features like no repetitive login, conversations linked with license, creating folders, selecting AI characters, and using your own API key. Users can enjoy a lifetime license with all future features included. The tool aims to simplify the process of interacting with ChatGPT and improving the overall user experience for software developers, wedding planners, and other professionals.

Innovation Acceleration is an AI-powered platform that empowers organizations to unlock their creative potential through the integration of advanced AI technologies and structured innovation frameworks. The platform offers a systematic and repeatable approach to creative thinking using Systematic Inventive Thinking (SIT) and Natural Language Processing (NLP) tools such as Large Language Models (LLMs) and generative AI (GenAI). Innovation Acceleration aims to accelerate the innovation process by guiding users through creating customized, industry-leading products, processes, strategies, and marketing innovations.

Poll the People is an AI-powered consumer research platform that offers 10X more effective surveys powered by ChatGPT. With a human panel of 500,000+ participants, the platform provides insights on brand testing, concept testing, logo testing, content testing, and more. By leveraging AI technology, users can make data-driven decisions, achieve faster insights, and access deep consumer understanding for better decision-making. The platform automates survey analysis, saving time and resources, and offers unbiased and accurate market insights. Poll the People is trusted by top brands worldwide for its efficiency and reliability in consumer research.

VisualEyes is a user experience (UX) optimization tool that uses attention heatmaps and clarity scores to help businesses improve the effectiveness of their digital products. It provides insights into how users interact with websites and applications, allowing businesses to identify areas for improvement and make data-driven decisions about their designs. VisualEyes is part of Neurons, a leading neuroscience company that specializes in providing AI-powered solutions for businesses.

Grand Studio is an AI design studio that specializes in UX design, digital products, strategy, and research. They use design thinking to tackle complex challenges and create innovative solutions for their partners. Their services include service design, qualitative research, product design and strategy, UX/UI design, and conversation design. Grand Studio aims to turn complexity into clarity by designing products, systems, and services that help users succeed. They work with a variety of partners across different industries to bring unique visions to life.

ProductScope is an AI-powered platform that enables e-commerce brands, marketers, and agencies to streamline product design and marketing efforts. It offers tools for creating engaging product visuals, gaining customer insights, and crafting SEO-friendly content to enhance brand visibility, conversions, and sales. With features like AI Photoshoot Tool, Amazon Chrome Extension, and Amazon Listing Optimizer, ProductScope helps users save time, money, and sell smarter with AI technology.

Hubble is an all-in-one user research platform designed to help uncover meaningful insights quickly and easily. It offers a wide range of features such as in-product research, contextual surveys, prototype testing, usability tests, participant recruitment, and resources like guides, templates, and demo videos. Trusted by product and research teams in world-class organizations, Hubble provides fast, scalable insights with industry-leading coverage of task types and surveys. With AI-powered research report building, quantitative data analysis, and easy exporting capabilities, Hubble aims to streamline the user research process and drive customer-centric decision-making.

Insight is an AI-powered medical research tool that serves as a research assistant for generating scientific summaries, hypotheses, experimental designs, and target identification. It empowers scientists to navigate literature, formulate hypotheses, and design experiments by utilizing peer-reviewed databases to provide reliable outputs. With integrated features like NIH PubMed access, NIH Reporter insights, and MYGENE & MYVARIANT deep dives, Insight streamlines the research process and accelerates discoveries in the medical field.

The IBM Power Systems AIX Collection provides modules to manage configurations and deployments of Power AIX systems, enabling workloads on Power platforms as part of an enterprise automation strategy through the Ansible ecosystem. It includes example best practices, requirements for AIX versions, Ansible, and Python, along with resources for documentation and contribution.

Awesome Responsible AI is a curated list of academic research, books, code of ethics, courses, data sets, frameworks, institutes, newsletters, principles, podcasts, reports, tools, regulations, and standards related to Responsible, Trustworthy, and Human-Centered AI. It covers various concepts such as Responsible AI, Trustworthy AI, Human-Centered AI, Responsible AI frameworks, AI Governance, and more. The repository provides a comprehensive collection of resources for individuals interested in ethical, transparent, and accountable AI development and deployment.

This repository aims to promote global equality for individuals pursuing a PhD in NLP by providing resources and information on various aspects of the academic journey. It covers topics such as applying for a PhD, getting research opportunities, preparing for the job market, and succeeding in academia. The repository is actively updated and includes contributions from experts in the field.

The 'machine-learning-research' repository is a comprehensive collection of resources related to mathematics, machine learning, deep learning, artificial intelligence, data science, and various scientific fields. It includes materials such as courses, tutorials, books, podcasts, communities, online courses, papers, and dissertations. The repository covers topics ranging from fundamental math skills to advanced machine learning concepts, with a focus on applications in healthcare, genetics, computational biology, precision health, and AI in science. It serves as a valuable resource for individuals interested in learning and researching in the fields of machine learning and related disciplines.

Awesome LLM for APR is a repository dedicated to exploring the capabilities of Large Language Models (LLMs) in Automated Program Repair (APR). It provides a comprehensive collection of research papers, tools, and resources related to using LLMs for various scenarios such as repairing semantic bugs, security vulnerabilities, syntax errors, programming problems, static warnings, self-debugging, type errors, web UI tests, smart contracts, hardware bugs, performance bugs, API misuses, crash bugs, test case repairs, formal proofs, GitHub issues, code reviews, motion planners, human studies, and patch correctness assessments. The repository serves as a valuable reference for researchers and practitioners interested in leveraging LLMs for automated program repair.

The 'awesome-ai4db-paper' repository is a curated paper list focusing on AI for database (AI4DB) theory, frameworks, resources, and tools for data engineers. It includes a collection of research papers related to learning-based query optimization, training data set preparation, cardinality estimation, query-driven approaches, data-driven techniques, hybrid methods, pretraining models, plan hints, cost models, SQL embedding, join order optimization, query rewriting, end-to-end systems, text-to-SQL conversion, traditional database technologies, storage solutions, learning-based index design, and a learning-based configuration advisor. The repository aims to provide a comprehensive resource for individuals interested in AI applications in the field of database management.

Kaapana is an open-source toolkit for state-of-the-art platform provisioning in the field of medical data analysis. The applications comprise AI-based workflows and federated learning scenarios with a focus on radiological and radiotherapeutic imaging. Obtaining large amounts of medical data necessary for developing and training modern machine learning methods is an extremely challenging effort that often fails in a multi-center setting, e.g. due to technical, organizational and legal hurdles. A federated approach where the data remains under the authority of the individual institutions and is only processed on-site is, in contrast, a promising approach ideally suited to overcome these difficulties. Following this federated concept, the goal of Kaapana is to provide a framework and a set of tools for sharing data processing algorithms, for standardized workflow design and execution as well as for performing distributed method development. This will facilitate data analysis in a compliant way enabling researchers and clinicians to perform large-scale multi-center studies. By adhering to established standards and by adopting widely used open technologies for private cloud development and containerized data processing, Kaapana integrates seamlessly with the existing clinical IT infrastructure, such as the Picture Archiving and Communication System (PACS), and ensures modularity and easy extensibility.

Fueling-Ambitions-Via-Book-Discoveries is an Advanced Machine Learning & AI Course designed for students, professionals, and AI researchers. The course integrates rigorous theoretical foundations with practical coding exercises, ensuring learners develop a deep understanding of AI algorithms and their applications in finance, healthcare, robotics, NLP, cybersecurity, and more. Inspired by MIT, Stanford, and Harvard’s AI programs, it combines academic research rigor with industry-standard practices used by AI engineers at companies like Google, OpenAI, Facebook AI, DeepMind, and Tesla. Learners can learn 50+ AI techniques from top Machine Learning & Deep Learning books, code from scratch with real-world datasets, projects, and case studies, and focus on ML Engineering & AI Deployment using Django & Streamlit. The course also offers industry-relevant projects to build a strong AI portfolio.

LLM4EC is an interdisciplinary research repository focusing on the intersection of Large Language Models (LLM) and Evolutionary Computation (EC). It provides a comprehensive collection of papers and resources exploring various applications, enhancements, and synergies between LLM and EC. The repository covers topics such as LLM-assisted optimization, EA-based LLM architecture search, and applications in code generation, software engineering, neural architecture search, and other generative tasks. The goal is to facilitate research and development in leveraging LLM and EC for innovative solutions in diverse domains.

CAMEL is an open-source library designed for the study of autonomous and communicative agents. We believe that studying these agents on a large scale offers valuable insights into their behaviors, capabilities, and potential risks. To facilitate research in this field, we implement and support various types of agents, tasks, prompts, models, and simulated environments.

Cool-GenAI-Fashion-Papers is a curated list of resources related to GenAI-Fashion, including papers, workshops, companies, and products. It covers a wide range of topics such as fashion design synthesis, outfit recommendation, fashion knowledge extraction, trend analysis, and more. The repository provides valuable insights and resources for researchers, industry professionals, and enthusiasts interested in the intersection of AI and fashion.

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.

Awesome-LLM-in-Social-Science is a repository that compiles papers evaluating Large Language Models (LLMs) from a social science perspective. It includes papers on evaluating, aligning, and simulating LLMs, as well as enhancing tools in social science research. The repository categorizes papers based on their focus on attitudes, opinions, values, personality, morality, and more. It aims to contribute to discussions on the potential and challenges of using LLMs in social science research.

Awesome Mobile LLMs is a curated list of Large Language Models (LLMs) and related studies focused on mobile and embedded hardware. The repository includes information on various LLM models, deployment frameworks, benchmarking efforts, applications, multimodal LLMs, surveys on efficient LLMs, training LLMs on device, mobile-related use-cases, industry announcements, and related repositories. It aims to be a valuable resource for researchers, engineers, and practitioners interested in mobile LLMs.

AI-PhD-S24 is a mono-repo for the PhD course 'AI for Business Research' at CUHK Business School in Spring 2024. The course aims to provide a basic understanding of machine learning and artificial intelligence concepts/methods used in business research, showcase how ML/AI is utilized in business research, and introduce state-of-the-art AI/ML technologies. The course includes scribed lecture notes, class recordings, and covers topics like AI/ML fundamentals, DL, NLP, CV, unsupervised learning, and diffusion models.

CodeLLM Paper repository provides a curated list of research papers focused on Large Language Models (LLMs) for code. It aims to facilitate researchers and practitioners in exploring the rapidly growing body of literature on this topic. The papers are systematically collected from various top-tier venues, categorized, and labeled for easier navigation. The selection strategy involves abstract extraction, keyword matching, relevance check using LLMs, and manual labeling. The papers are categorized based on Application, Principle, and Research Paradigm dimensions. Contributions to expand the repository are welcome through PR submission, issue submission, or request for batch updates. The repository is intended solely for research purposes, with raw data sourced from publicly available information on ACM, IEEE, and corresponding conference websites.

This repository serves as a comprehensive hub for updates on generative AI research, interview materials, notebooks, and more. It includes monthly best GenAI papers list, interview resources, free courses, and code repositories/notebooks for developing generative AI applications. The repository is regularly updated with the latest additions to keep users informed and engaged in the field of generative AI.

I'm the Mixed Methods Design Decision Tool, offering guidance on mixed methods research designs, their implementation, and effective communication in studies.

I'm Qualitative Quest, here to offer concise advice on qualitative research methods, analysis techniques, and tools.

The AI mentor for medical education research

Expert in health qualitative research and thematic analysis.

This GPT chat AI is specialized in understanding Extractables and Leachables studies, aligning with pharmaceutical guidelines, and aiding in the design and interpretation of relevant experiments.

Especialista em dados de pós-graduação em Arquitetura e Urbanismo.

A bio-inspired design and research assisant guiding innovative solutions using the Biomimicry Institute design process.

Doing art design and research, including fine arts, audio arts and video arts, designed by Prof. Dr. Fred Y. Ye (Ying Ye)

A UX research assistant focused solely on UX research and design.

UX Design, UX Architecture & User Research Expert with a focus on collaborative, user-centered methods and achieving business goals.

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

Expert in physics-informed neural networks for practitioners

Expert in loudspeaker design and acoustic theory.

AI expert in UX Research and User Interviews

Improves product quality through innovative research and development.

Guides scientific discovery through experimental research strategies.

A helpful guide for biochemical engineers, offering insights and reassurance.

High School Science Research Mentor

I improve marketing effectiveness by designing stunning research-led assets in a flash!

Expert in disease cures, medical research, and data analysis.