Find the right tools for your research

⁠Neurist is an AI-forward platform for end-to-end market research, orchestrating the full research lifecycle through frontier language models, conversational AI and real-time synthesis into a unified intelligence system. Built for the era of compound AI, Neurist replaces fragmented, labor-intensive research workflows with a continuously learning intelligence layer that transforms conversational data into structured, decision-ready knowledge - empowering teams to run high-fidelity research at scale, extract deep customer intelligence from unstructured feedback, and compress the cycle from raw signal to strategic clarity. By democratizing access to enterprise-grade qualitative research, Neurist enables organizations to build a living corpus of customer intelligence that compounds in value across every study and conversation.

Versive is an AI customer research platform that helps teams conduct and analyze research faster. Companies like Udacity and IDEO use our conversational surveys, usability tests, and AI synthesis to get faster, richer insights.

Perceptional is an AI-moderated user interview platform that allows product teams to deploy an engaging, context-aware chatbot to conduct qualitative user interviews. Perceptional bridges the gap between in-depth (but time-consuming) user interviews and scalable (but shallow) online surveys, allowing teams to more efficiently gather and process qualitative data. As responses are collected, Perceptional uses AI to synthesize them into key findings, summaries, themes, and much more. Our customers have experienced 10x faster product research projects compared to 1-on-1 interviews and 4x more insights compared to traditional online surveys. And most importantly, Perceptional is designed to supplement, not replace, user interviews.

At Crowd, we're passionate about understanding the language of your users. This platform is more than just a research tool; it's the bridge to building meaningful connections between businesses and their customers. With Crowd's amazing features, understanding your users becomes an exciting adventure rather than a daunting task.

Glaut's AI-moderated interviews engage respondents in realistic conversations that adapt to their responses and probe deeper to uncover more details behind their thoughts. We give you the power to interview thousands of respondents simultaneously, across multiple languages, with minimal effort. And we don’t stop there! Glaut super-power is about transcribing the data, extracting themes, key verbatims and insights to produce an actionable report that effectively answers to your research objectives, in a fraction of time compared to the current market practice.

Dialogue is an AI-native customer research platform that helps companies truly understand their customers. We make it possible to source participants, run hundreds or thousands of live, adaptive interviews at scale, and synthesize insights in real time. Our mission is simple: make listening effortless—so whether you’re a researcher, marketer, designer, or engineer, you can make smarter decisions faster. Real insights. Real people. Research for everyone.

Whyser is a research platform that conducts AI-moderated user interviews on your behalf—so you can uncover qualitative insights at scale in hours instead of weeks. Make qualitative research happen when it otherwise wouldn’t. Whyser can also complement your quantitative research by unlocking the qualitative “why” behind participant behavior. Together, they create a powerful mixed-methods research workflow.

m-Path empowers researchers to capture human experience as it unfolds in real time. Whether you're conducting ecological momentary assessment (EMA), experience sampling (ESM), daily diary research, or other forms of intensive longitudinal data collection, m-Path provides everything you need in one flexible platform. Easily integrate passive mobile and wearable sensing, context-aware triggering, or deliver ecological momentary interventions (EMIs) and just-in-time adaptive interventions (JITAIs), all without writing a single line of code. Our intuitive study builder dashboard lets you mix and match powerful features to design the perfect protocol for your research question. Collect data seamlessly across iOS and Android devices and gain deeper insight into people’s real-world behavior and experiences.

Maze began with the belief that product design teams should have easy access to data during the design phase. Since then we have evolved our vision to empower anyone in product and marketing teams to test, learn, and act rapidly. We believe that this is how you build successful user experiences today.

We make customer insights, brand / marketing execution, and measurement better, faster, and cheaper using an innovative AI platform and advanced behavioural change technology Brand owners and marketers benefit in 3x ways: #1 — Customer & behavioural insights • Gather rich behavioural insights from your target customers—identifying your brand’s unique choice drivers, barriers, FAQs, pain points and more • Determine the rational and non-rational factors that drive (or inhibit) behaviour change #2 — Behaviourally optimised content creation • Rapidly create powerful, behaviourally optimised marketing content designed to convert • Integrate your choice drivers, emotions, brand evidence, and use proven behavioural science tools to drive behaviour change #3 — Strategic brand & marketing comms measurement • Discover and track your brand (or campaign) performance on key behavioural drivers, determine brand and ad awareness, and business outcomes • Gain diagnostic, actionable insight into primary marketing communications and/or operational challenges to overcome • Ensure your business activities and marketing communications address the true reasons that drive (or inhibit) your brand growth

Mabyduck makes it easy to create and run studies that evaluate the quality of AI-generated content, including audio, images, video, and interactive experiences. The platform handles data hosting, rater pre-screening, study monitoring, and real-time results visualization—so you can focus on improving your AI models.

Build accurate language models with human and AI feedback. The feedback loops you need to fine-tune, validate, and maintain enterprise LLMs.