stratify
Stratify runs AI-led user research end to end — recruitment, interviews, and analysis in hours, not weeks.
Stratify is worth a demo if your bottleneck is research turnaround, not research rigor. The AI interviewer plus built-in panel compresses design-to-insight into hours, and the free five-minute landing page test lets you judge the interview quality before you talk to sales. Against UserTesting or dscout, you gain speed and consolidation but give up transparency — pricing is demo-gated and documented integrations are sparse. Buy it for fast, repeatable concept and landing-page validation; don't buy it if you need deep qualitative interpretation or a documented API surface.
Verified 4d ago · liveness 55/100 · cite: rightaichoice.com/tools/stratify
- Product teams validating features and user flows before launch
- UX researchers conducting scalable user interviews
- Marketers testing messaging, campaigns, and landing pages
- Startups needing fast feedback loops without heavy research process
- Teams requiring on-premise or private cloud deployment
- Researchers needing deep qualitative analysis and thick description
- Buyers who need self-serve or publicly listed pricing
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Skip Stratify if you need publicly listed pricing, a documented API and integrations to plug research into an existing toolchain, or human-moderated depth interviews rather than AI-led structured sessions.
Pricing is only quoted after a demo request, so you cannot budget from the website — expect a sales conversation before you know your per-study cost.
Stratify prices as a demo-gated B2B research platform, which typically fits funded startups and mid-market product, UX, and marketing teams rather than solo researchers or bootstrapped teams hunting a free tier. Against UserTesting or dscout, the pitch is consolidation — recruitment, interviews, and analysis in one line item. Budget-constrained buyers should compare against self-serve alternatives; larger orgs should ask about seat minimums and annual terms on the demo call.
In short
stratify — Stratify runs AI-led user research end to end — recruitment, interviews, and analysis in hours, not weeks. Best for Product teams validating features and user flows before launch, UX researchers conducting scalable user interviews, Marketers testing messaging, campaigns, and landing pages. Contact Sales pricing.
What people actually say about stratify — is it worth it?
We scanned public community sources for stratify on Jul 3, 2026 and could not establish that the discussion we found is about this tool rather than something else sharing its name. Our own analysis of that scan says the posts were off-subject. Rather than publish a sentiment score built on the wrong subject, we publish nothing here and re-run the scan.
Viability Score
How well maintained and how widely used is stratify? 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: October 2026
How we score →Key Features
- AI interviewer runs autonomous research sessions
- Generates comprehensive interview guides in minutes
- Import existing questions or let AI craft the interview flow
- Methodology-adaptive question structuring
- Upload websites, prototypes, images, videos, or ad copy for review
- Captures participant screen and video in real time
- Intelligent Analysis Engine synthesizes feedback into patterns
- Built-in participant panel for recruitment
- Free sample landing page test — about 5 minutes, no signup
- End-to-end automation from recruitment to insights
- Targeted solutions for product, UX, and marketing teams
- Real-time feedback collection during sessions
- Video and screen recording of user responses
- Backed by Y Combinator
About stratify
Stratify is an AI-powered user research platform that automates the whole research loop: designing the study, recruiting participants, running the session, and synthesizing the findings. You upload the thing you want reviewed — a website, prototype, image, video, or ad copy — and Stratify's AI interviewer captures the participant's screen and video while they respond in real time. Study design is handled by an AI that generates a comprehensive interview guide in minutes; you can import your existing questions or let the AI build a flow tailored to your research objectives. Once sessions run, the Intelligent Analysis Engine turns raw responses into patterns and reports you can act on. The platform is built around three buyer groups: product teams validating features and user flows before launch, UX researchers running scalable interviews, and marketers testing messaging, campaigns, and landing pages. A built-in participant panel covers recruitment, so you are not sourcing respondents separately. There is also a free sample landing-page test that takes about five minutes and requires no signup, so you can see how the AI interviewer behaves before requesting a demo. Stratify is backed by Y Combinator, and Human Behavior Co. (YC X25) is cited as using it to run customer research on autopilot. Compared to tools like UserTesting or dscout, Stratify's pitch is consolidation — recruitment, interview design, execution, and analysis in one platform. The trade-offs are real: pricing is gated behind a demo request, and documented integrations are sparse, so teams with a deep existing toolchain should check fit carefully.
Behind the Verdict
Stratify's real product is the handoff between steps. Traditional research tooling breaks the workflow into separate purchases — a panel vendor for recruiting, a testing tool for sessions, a spreadsheet or analysis tool for synthesis. Stratify collapses those into one pipeline: you point the AI at a website, prototype, image, video, or ad copy, it runs an autonomous interview and records the participant's screen and video, then the Intelligent Analysis Engine turns responses into patterns. For product teams under pressure to ship, that compression is the whole value proposition. The study-design layer is the second differentiator. Rather than starting from a blank question list, you either import your own or let the AI generate a comprehensive interview guide, structured around your methodology and research objective. That lowers the skill floor considerably — a PM who has never written a discussion guide can get a usable one in minutes. The vendor claims an 80% faster time to insights and a 2-hour average research completion for product teams, alongside stats on failed features and the cost of building the wrong thing; treat those numbers as vendor-supplied framing rather than independent benchmarks. The weaknesses are operational, not conceptual. Pricing sits behind a demo request, which means budget-conscious teams cannot self-qualify, and there is no published tier list to compare against UserTesting or dscout. Documented integrations are thin — the product-team page even lists "Can I integrate Stratify with my existing tools?" as an FAQ without a visible answer surface in the scrape — so if your workflow depends on piping research into Notion, Slack, or a data warehouse, validate that before committing. Finally, an AI interviewer is a structured instrument: it will surface patterns efficiently, but researchers who need thick, open-ended qualitative description may find the format constraining. The honest read is that Stratify is excellent for fast, directional validation and less suited to deep ethnographic work — and you should confirm current pricing, security posture, and data-handling answers directly on a demo call.
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Real-world workflow fit
Concrete scenarios for the personas stratify actually fits — and what changes day-one when you adopt it.
You have a feature concept and three weeks before the sprint locks. You upload a clickable prototype, let Stratify's AI generate the interview guide from your research objective, and run sessions through the built-in panel.
Outcome: You get pattern-level findings on the concept before committing engineering time, instead of waiting 3-6 weeks for a manual study.
You need to find onboarding friction fast. You upload the live onboarding flow, run AI-led interviews that capture participants' screens and video, and review the Intelligent Analysis Engine's synthesis of where users get stuck.
Outcome: Friction points are identified and turned into retention and support-ticket fixes without manually moderating every session.
You have four landing page variants and ad copy to test. You run each through Stratify and use the free five-minute sample test first to sanity-check how the AI interviewer behaves.
Outcome: You pick messaging based on target-user reactions rather than internal opinion, ahead of spending on paid traffic.
Use Cases
- Validate product features and user flows with real user feedback before launch.
- Test landing page copy and design with target users to improve conversion.
- Run scalable UX interviews to identify friction points in onboarding.
- Evaluate ad creatives and video prototypes quickly.
- Prioritize features based on actual user needs rather than internal assumptions.
- Gather rapid customer insights for product roadmap decisions.
Limitations
- Pricing details are not shown in the scraped evidence, so budget-conscious teams cannot self-qualify tiers from the page alone.
- No integrations or API documentation are surfaced in the evidence, so workflow-automation fit cannot be assessed without a demo conversation.
- The study flow is AI-led recruitment, interviewing, and analysis, so depth of qualitative interpretation may be constrained versus human-moderated research.
as of 2026-09-14
Verification history
We have re-verified stratify 9 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.
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
Showing the 6 most recent of 9 verification passes.
Free to cite with attribution — this page re-verifies continuously.
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 stratify's pricing actually pencils out — and where peers do it cheaper.
Stratify prices as a demo-gated B2B research platform, which typically fits funded startups and mid-market product, UX, and marketing teams rather than solo researchers or bootstrapped teams hunting a free tier. Against UserTesting or dscout, the pitch is consolidation — recruitment, interviews, and analysis in one line item. Budget-constrained buyers should compare against self-serve alternatives; larger orgs should ask about seat minimums and annual terms on the demo call.
Setup time & first value
How long it actually takes to get something useful out of stratify — broken out by persona, not the marketing-page minute.
Product teams: expect roughly an afternoon from demo request to first study — the AI drafts the interview guide in minutes and the built-in panel handles recruitment. Researchers: budget a day to align the AI-generated guide with your methodology before running sessions. Marketers: fastest path is the free 5-minute sample landing page test, which needs no signup and shows you the AI interviewer's
Switching to or from stratify
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From UserTesting: upload the same assets (prototype, site, ad copy) and let Stratify's AI generate the guide, consolidating recruitment and analysis into one platform.
- →From dscout: move structured concept and landing-page studies to Stratify's AI interviewer to cut the manual design and synthesis steps.
- ↗To UserTesting: if you need human-moderated sessions and a broader enterprise research toolchain, export your study assets and rebuild the studies there.
- ↗To dscout: if your work depends on deep qualitative diary or field research, that format fits dscout's model better than an AI-led structured interview.
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “stratify”, and we withheld 6: 6 could not be judged, because “stratify” 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 stratify.
Official links
Tools that pair well with stratify
Common stack mates teams adopt alongside stratify, with the specific reason each pairing earns its keep.
Maze
User research platform that combines participant recruitment, AI-moderated interviews, and automated analysis in one workspace
Versive
AI research platform that runs interviews, surveys, and usability tests with real and synthetic users in one study.
Marvin User Research
Marvin is an AI-native customer insights platform that runs AI-moderated interviews and delivers cited answers from your research repository.
Featured Head-to-Head Comparisons
Stratify vs Praktika
Praktika and stratify serve completely different needs—language practice vs. user research. Choose Praktika if you're a language learner wanting AI conversation partners with feedback; choose stratify if you're a product team needing fast, scalable user interviews. No direct competition; decision hinges entirely on your domain.
Stratify vs Surge Ai
Stratify and Surge AI serve completely different needs. Stratify is for product teams wanting fast, automated user research with AI-conducted interviews. Surge AI is for AI builders needing expert human feedback to align and evaluate frontier models. Choose based on whether you need insights from users or expert feedback for models.
Gem vs Stratify
Gem and Stratify serve entirely different domains: recruiting vs. user research. If you need an all-in-one hiring platform with AI agents for sourcing, screening, and fraud detection, Gem is the clear choice. If your goal is to automate user interviews and gather product feedback in hours, Stratify is purpose-built for that. There is no head-to-head competition—pick based on your primary workflow.
Alternatives to stratify
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Maze
User research platform that combines participant recruitment, AI-moderated interviews, and automated analysis in one workspace
Versive
AI research platform that runs interviews, surveys, and usability tests with real and synthetic users in one study.
Marvin User Research
Marvin is an AI-native customer insights platform that runs AI-moderated interviews and delivers cited answers from your research repository.
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