Maze is a continuous product discovery platform whose AI analyzes user research, tests prototypes and surfaces insights at scale.
Maze lets teams run usability tests, surveys and interviews, then uses AI to synthesize the results into themes and reports. Its AI reports cluster open-text feedback, summarize interview transcripts and highlight what matters to stakeholders. Prototype tests integrate with Figma so design validation fits the existing workflow. Product teams use Maze to make user research a weekly habit rather than a quarterly project.
Maze offers a free plan with limited studies; paid plans add AI features, advanced testing and team collaboration options.
Product designers, researchers and product managers who need continuous user feedback without research bottlenecks.
Yes, a free plan exists; AI analysis and higher study limits require paid plans.
Yes. Maze provides integrations and APIs for connecting research data with product tools.
Maze covers the full loop from test design to AI synthesis, where survey tools stop at raw response collection.
Product teams test Figma prototypes with recruited participants and get AI-clustered feedback themes within hours. Researchers run continuous discovery programs with weekly micro-tests. PMs share auto-generated insight reports with stakeholders who skip raw data. Teams build a searchable research repository as studies accumulate.
Participant quality varies with the panel, and advanced testing needs paid plans. Quant-heavy programs may need complementary analytics. UserTesting, Lookback and Dovetail compete in user research platforms.
Maze integrates with Figma, Sketch and Adobe XD for prototype testing, and with collaboration tools for sharing insights. Recruitment panels supply participants, or teams test their own users. AI analysis runs on collected responses, generating reports in-platform. Workspace setup covers study templates, permissions and research repositories. Ongoing operations manage participant budgets, maintain research libraries and feed insights into product planning cycles.
Maze turns user research from a periodic project into a continuous habit, and its AI synthesis saves hours per study. Participant quality varies, and advanced features cost extra. Product teams committed to discovery will get strong returns.