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Maze

by Maze

AI Application
Low Confidence

Maze (Maze.Design Inc.) is an AI-powered user research and testing platform that brings continuous user and market research behind product decisions. It offers research-grade AI (AI Moderator, AI Study Builder, AI-powered analysis and automated reporting) that assists qualitative and quantitative research across every stage: participant recruitment (a panel of 6M+ participants or a team's own community), usability testing, prototype testing, moderated interviews, surveys, card sorting, tree testing, concept testing, live website and mobile testing. Researchers and product teams use Maze to recruit the right people, run rigorous studies, and turn findings into reports, clips and highlights. The platform also provides an MCP server to bring research into the tools teams use daily. Intended users include UX researchers, product managers, designers, and market researchers. Evidenced use cases: concept validation, usability testing, copy testing, user satisfaction, market research.

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Transparency Score

Weighted across four pillars · updated October 12, 2026

Overall grade
30% weighted
ABCDF

Capabilities

Ai Moderated Interviews
Participant Recruitment
Prototype Testing
Surveys
Usability Testing
Qualitative Analysis
Synthesis
Report Generation
Conversation

AI Models

Underlying AI models powering this application

★GPT
Claude
Deepgram ASR
Gemini

Vendor Information

Complete information about the vendor/provider of this AI application

MazeView all products →
Maze.Design Inc.(Trading as: Maze)
Contact Information
maze.co
Registered Address
800 Menlo Ave, Suite 220, Menlo Park, California, 94025, United States

Infrastructure

Platforms hosting this application — each inherits its own transparency grade.

Amazon Web Services (AWS)
Amazon
F
View full infrastructure →

EU AI Act Provider Information

Verification Status:
Unverified
Maze.Design Inc.(Trading as: Maze)
800 Menlo Ave, Suite 220, Menlo Park, California, 94025, United States
Compliance Documents
Instructions for Use
Maze's AI systems may introduce hidden bias in data or models, leading to patterns or insights that drift from participant input without clear warning. The vendor advises labeling AI-assisted outputs, reviewing AI-generated themes against original data, and disclosing AI involvement to participants due to risks like biased prompts or overconfident summaries. (Source: Maze AI ethics guidance for UX research.)
Compliance & Risk

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Added: October 10, 2026
Updated: October 12, 2026

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