Maze is live · custom pricing · last verified 8 Nov 2026 · viability healthy
Maze
Maze is a user research platform for prototype testing, surveys, interviews, and AI-assisted analysis at scale.
Pick Maze when research is a standing team function — one workspace for panel recruitment, prototype tests, surveys, and interviews beats stitching three tools together. Read the feature table before you promise anyone AI Study Builder, AI Moderator, or Maze MCP; those are Enterprise rows. For sporadic prototype testing, Lyssna costs far less.
Verdict generatedVerified 5d ago · liveness 77/100 · cite: rightaichoice.com/tools/maze
- Product teams running mixed-method research — surveys, interviews, prototype tests — in one workspace
- Design teams validating Figma, Sketch, or Adobe XD prototypes with automated reporting
- Enterprises putting research in the hands of PMs and designers instead of queuing for the research team
- Research teams that want AI to draft guides, transcribe sessions, and surface themes across studies
- Teams that only run occasional prototype tests — Lyssna costs far less for that job
- Researchers doing deep line-by-line qualitative coding — Dovetail fits that shape better
- Organizations needing offline, on-premise, or self-hosted deployment — Maze is cloud-only
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Skip Maze if you mainly need cheap, self-serve prototype tests and won't use panel recruitment, moderated interviews, or automated reporting — you'd be paying for a research system you don't run.
AI Moderator, AI Study Builder, interview studies, panel recruitment, the Maze mobile app, and AI survey analysis are tagged Enterprise on the pricing page, so the all-in-one pitch costs more than the All-plans entry
Maze is priced for organizations where research is a recurring function, and the tier split matters more than the headline: AI Moderator, AI Study Builder, interview studies, panel recruitment, and the mobile app are Enterprise, while prototype testing, card sorting, surveys, and automated reporting are All plans. If your need is one-off prototype testing, Lyssna is dramatically cheaper; if it's transcript coding, Dovetail is the narrower, cheaper fit.
In short
Maze — Maze is a user research platform for prototype testing, surveys, interviews, and AI-assisted analysis at scale. Best for Product teams running mixed-method research — surveys, interviews, prototype tests — in one workspace, Design teams validating Figma, Sketch, or Adobe XD prototypes with automated reporting, Enterprises putting research in the hands of PMs and designers instead of queuing for the research team. Pricing is on request (custom quotes).
No head-to-head comparison for Maze yet — the alternatives below are the closest matches we list.
What is Maze?
Maze — Maze is a user research platform for prototype testing, surveys, interviews, and AI-assisted analysis at scale. Best for Product teams running mixed-method research — surveys, interviews, prototype tests — in one workspace, Design teams validating Figma, Sketch, or Adobe XD prototypes with automated reporting, Enterprises putting research in the hands of PMs and designers instead of queuing for the research team. Pricing is on request (custom quotes).
Maze bundles the whole research loop into one account: recruit, run the study, analyze, report. Participants come either from a panel of over 6 million (the pricing page still rounds that to 'over 5 million') or from your own community via in-product prompts, with smart screener questions and B2B/B2C targeting to filter out the wrong people. Method coverage is deliberately wide — prototype testing, live website and mobile testing, moderated interviews, surveys, card sorting, and tree testing — so qualitative and quantitative work don't need two vendors. AI sits in the build and analysis stages rather than replacing judgment. AI Study Builder takes a written research goal and returns a launch-ready study; AI Moderator drafts a structured discussion guide from your context; interview transcription runs automated theme analysis, and AI survey analysis handles open text. Automated reports bundle clips, highlights, and stats, results are embeddable, and Maze MCP pushes research into Claude, ChatGPT, Gemini and other tools the team already uses. Security is spelled out: SOC 2 Type II, SSO, role-based access and private workspaces, fully encrypted transmission, GDPR alignment, and a stated commitment not to train AI on your research data. If you're the one signing the vendor review, that page answers most of the questionnaire. The fit is product teams, designers, PMs, and researchers who want research to be a standing habit instead of a quarterly project. The catch is the tier table: Maze MCP, AI Study Builder, AI Moderator, interview studies, and the Maze mobile app sit on Enterprise, while prototype testing, card sorting, automated reporting, and panel recruitment are marked all-plans. Compare against Lyssna for cheap occasional prototype tests and Dovetail for deep qualitative coding.
Key features
- AI Study Builder turns a written research goal into a ready-to-launch study
- AI Moderator drafts a structured discussion guide from your research context
- Prototype testing for Figma, Sketch, and Adobe XD prototypes
- Live website testing on real pages
- Mobile testing via the Maze mobile app
- Moderated interview studies with scheduling and AI moderator
- Interview transcription with automated theme analysis
- Interview clips, call transcripts, and highlights in reports
- Surveys with AI survey assistance and AI survey analysis
- Open and closed card sorting for IA and naming decisions
- Tree testing to validate information architecture
- Panel recruitment from an international participant panel with demographic filters
- In-product prompts to recruit from your own user community
- Smart screener questions with B2B and B2C targeting
- Maze MCP server pushing research into Claude, ChatGPT, Gemini, and other AI tools
Behind the verdict
Where Maze earns its seat is continuity. Studies accumulate in one place, the panel and your own community share the same recruiting flow, and reports stay embeddable so findings actually get looked at. If your team reruns usability tests every sprint and wants PMs running studies without a researcher babysitting every step, that compounding loop is the real product. We'd reach for it when the bottleneck is logistics. Panel targeting, screener questions, interview scheduling, transcription, and theme analysis under one roof removes the spreadsheet-and-Calendly tax that quietly kills research cadence. Where it bites is packaging. AI Study Builder, AI Moderator, moderated interview studies, Maze MCP, and the mobile testing app are listed on the Enterprise side, so a growth-stage team that bought in for prototype testing may find the AI features that sold them are gated. Check the compare-features table line by line before you plan headcount around any of it. Pricing isn't posted — you'll talk to sales, which also means annual commitments and procurement cycles. Method-wise, the gaps are real. Diary studies, longitudinal field research, and heavy ethnographic work aren't in the set. Researchers who want line-by-line qualitative coding with a codebook will find Maze's automated theme analysis a starting point, not a replacement — Dovetail remains the deeper qualitative tool, and pairing the two is a common pattern. On the cheap end, if all you do is a handful of prototype tests a quarter, Lyssna's pricing is easier to justify. Maze's value scales with volume and team count. The caveat I'd flag most: AI-drafted guides and AI-moderated sessions are useful drafts, not finished instruments. Teams that treat the generated discussion guide as final ship weaker interviews.
Models under the hood
as of 2026-11-08
Limitations
- The pricing page splits capabilities between All plans and Enterprise, and the Enterprise list is where the headline features live: AI Moderator, AI Study Builder, interview studies, panel recruitment, the Maze mobile app, and AI survey analysis.
- Prototype testing, card sorting, automated reporting, and surveys are the All-plans side.
- Limits apply to AI features and panel usage depending on plan.
- The vendor quotes its participant panel inconsistently — over 6 million on the homepage, over 5 million on the pricing page.
- The evidence names no underlying AI model behind Maze AI.
- Maze MCP is presented as a new capability with no stated stability or availability guarantees.
- Deployment is cloud-only on AWS; there is no offline or self-hosted option.
- Diary studies are not part of the documented method set.
as of 2026-10-20
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Is Maze still active?
Maze is live · custom pricing · last verified 8 Nov 2026 · viability healthy.
Viability score
How well maintained and how widely used is Maze? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: November 2026
How we score →What do users say about Maze?
What people actually say about Maze — is it worth it?
Our community sentiment research written Jul 26, 2026 is more than 90 days old, so it is being re-reviewed against current data and is not shown.
How we verified this
Every listed fact about Maze — pricing, features, links, status — is re-read from the vendor's own pages by our verification pipeline and each change is logged with a date; the last pass ran on 8 Nov 2026. Analysis is drafted with AI models and checked against our editorial standards before publishing; see how we verify.
Verification history
We have re-verified Maze 22 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — changed pricing page, who should skip it, description, summary, our verdict, pricing tiers, features
- — changed summary, pricing tiers, features, who it suits, our verdict, description, who should skip it
- — changed pricing page
- — changed summary, who should skip it, pricing tiers, features, our verdict, who it suits, description, integrations
- — changed our verdict, setup time, who should skip it, description, who it suits, features, use cases, hidden costs, integrations, limitations, switching in, summary, switching out, pricing tiers, pricing fit
- — changed description, features, who it suits, who should skip it, our verdict, integrations, summary
Showing the 6 most recent of 22 verification passes.
Free to cite with attribution — this page re-verifies continuously.
How much does Maze cost in 2026?
Maze: Pricing is on request (custom quotes). Pricing last verified 8 Nov 2026.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Where the pricing makes sense
The company stage and team size where Maze's pricing actually pencils out — and where peers do it cheaper.
Maze is priced for organizations where research is a recurring function, and the tier split matters more than the headline: AI Moderator, AI Study Builder, interview studies, panel recruitment, and the mobile app are Enterprise, while prototype testing, card sorting, surveys, and automated reporting are All plans. If your need is one-off prototype testing, Lyssna is dramatically cheaper; if it's transcript coding, Dovetail is the narrower, cheaper fit.
Has Maze's pricing changed?
No plan price for Maze has moved since we began logging in Aug 2026; the pricing page is re-read on every verification pass.
Who should pick Maze?
Pick Maze if you are Product teams running mixed-method research — surveys, interviews, prototype tests — in one workspace, Design teams validating Figma, Sketch, or Adobe XD prototypes with automated reporting, Enterprises putting research in the hands of PMs and designers instead of queuing for the research team, Research teams that want AI to draft guides, transcribe sessions, and surface themes across studies.
Look elsewhere if you are Teams that only run occasional prototype tests — Lyssna costs far less for that job, Researchers doing deep line-by-line qualitative coding — Dovetail fits that shape better, Organizations needing offline, on-premise, or self-hosted deployment — Maze is cloud-only, Teams whose core method is diary studies or heavy field research outside Maze's method set.
Skip it if Skip Maze if you mainly need cheap, self-serve prototype tests and won't use panel recruitment, moderated interviews, or automated reporting — you'd be paying for a research system you don't run.
GeneratedReal-world workflow fit
Concrete scenarios for the personas Maze actually fits — and what changes day-one when you adopt it.
You have a Figma prototype for a new onboarding flow and two days before the design review. You launch a prototype test in Maze, recruit from your own user base with a screener, and let Maze AI cluster the open-text answers into themes.
Outcome: You walk into the review with a shareable automated report — clips, highlights, and clustered themes — instead of three anecdotal Slack quotes.
You need moderated interviews but scheduling eats your week. You use Maze's interview scheduling and AI Moderator to draft the discussion guide from your research goal, then rely on transcription and automated theme analysis instead of re-watching recordings.
Outcome: Analysis time drops, and findings reach PMs through reports and the Maze MCP connection into the AI tools your team already uses.
Navigation is up for a rebuild and you want evidence before engineering commits. You run a tree test and a closed card sort with panel participants targeting your actual customer demographics.
Outcome: You get data on how users group and name things, at All-plans tier, before any code is written.
Use cases
- Run a five-second or concept test on landing page variants and pick a winner without a research ops cycle.
- Test a Figma prototype with real users in days and let Maze AI cluster the open-text responses into themes.
- Run AI-moderated interviews where the moderator asks follow-ups based on what the participant said.
- Validate information architecture with a tree test before committing engineering time to a rebuild.
- Recruit B2C or B2B participants from the panel when you need a study on short notice.
- Embed automated research reports into Notion or Jira so PMs see findings where they already work.
- Track customer needs and category signals over time against a research baseline.
- Democratize research so PMs and designers run studies themselves instead of queueing for the research team.
Setup time & first value
How long it actually takes to get something useful out of Maze — broken out by persona, not the marketing-page minute.
A prototype test can be live in under an hour if you already have a Figma file and your own participants. Plan a day for your first study with panel recruitment and screeners, since targeting and quota setup take the most thought. Enterprise AI Moderator and AI Study Builder setups depend on your sales and onboarding process, not on the product.
Switching to or from Maze
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From UserTesting: rebuild your moderated interview scripts as Maze interview studies, then move recruiting to Maze's panel or your own in-product prompts.
- →From Lyssna: rebuild prototype tests against your Figma, Sketch, or Adobe XD files, then set up automated reporting to replace manual result wrangling.
- →From Google Forms or Typeform surveys: recreate the survey in Maze so responses land in the same workspace as your usability and IA tests.
- →From Dovetail: keep Dovetail if deep transcript coding is the core need, or move interview recording and theme analysis into Maze's AI analysis and reports.
- ↗To Lyssna: if your work is only prototype tests, export your results and rebuild tests in Lyssna to cut license cost.
- ↗To Dovetail: if line-by-line qualitative coding becomes the core of your work, export interview transcripts and recordings into Dovetail.
- ↗To UserTesting: if you need a moderated-session-first workflow with its own panel, plan for re-recruiting participants and rebuilding study scripts.
Integrations
Resources & guides
Tutorials & Learning
YouTube returned 6 videos for “Maze”, and we withheld 6: 6 could not be judged, because “Maze” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Maze.
Official links
What are the best Maze alternatives?
The closest alternatives to Maze we list are UserTesting AI, stratify and Articos. Ranked by direct product-type match, not category overlap.
| Alternative | Pricing | Starts at | Last verified |
|---|---|---|---|
| UserTesting AI | Contact Sales | Custom pricing | — |
| stratify | Contact Sales | Custom pricing | — |
| Articos | Freemium | Pricing not published | — |
Alternatives to Maze
View all
UserTesting AI
UserTesting AI pairs AI test creation and evidence-linked Insight Summaries with a 6M+ human research panel.
Tools that pair well with Maze
Common stack mates teams adopt alongside Maze, with the specific reason each pairing earns its keep.
UserTesting AI
UserTesting AI pairs AI test creation and evidence-linked Insight Summaries with a 6M+ human research panel.
stratify
Stratify runs AI-led user research end to end — recruitment, interviews, and analysis in hours, not weeks.
Articos
Articos runs AI-moderated synthetic user interviews and returns a structured research report in about 30 minutes.
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