sunzu.com valid
Sunzu
Sunzu is AI user research software. Shape products people love. User insights in minutes. Test ideas, designs and ads 500× faster than human research. Cut research costs. Let every team test and learn.
- Authority
- 47 reach 6 · trust 5 · quality 21 · freshness 15
- Tier
- listed
- llms.txt
- https://sunzu.com/llms.txt
- Sections
- 6
- Links
- 41
- Size
- 8336 bytes
- Popularity rank
- #518107
- Registered
- 2004-07-18
- Country
- — Publisher location unknown; CDN address excluded
- Country evidence
- No published address evidence collected yet
- For agents
- Documentation: developer or product docs worth reading, nothing to call
- First seen
- 2026-10-19T10:43:49.132Z
- Last checked
- 2026-10-21T05:30:55.463Z
- Badge
Their llms.txt
The beginning of the file, from our validated copy saved 2026-10-21T05:30:55.012Z. Cached copy · Source on sunzu.com
# Sunzu
> Sunzu is AI user research software. Shape products people love. User insights in minutes. Test ideas, designs and ads 500× faster than human research. Cut research costs. Let every team test and learn.
© 2026 Sunzu, Inc. All rights reserved. Services outside the UK, Switzerland and EEA are provided by Sunzu, Inc., a Delaware corporation (file #10756833). UK, Swiss and EEA services are provided by its wholly owned subsidiary, Alpha Base OS Ltd, registered in England and Wales (company #16212608; registered office: 71–75 Shelton Street, Covent Garden, London WC2H 9JQ, United Kingdom; VAT GB488054656; ICO C1103931).
## Product and evidence
- [Research, definitions and benchmark scope](https://sunzu.com/research/): how audiences work, the evidence base, validation and limits. Guide updated 2026-09-29; study benchmarks reviewed 2026-09-08.
- [Product website](https://sunzu.com/): study workflows, customer testimonials and booking.
- [Web app demo](https://sunzu.com/videos/web-app/): explore the browser workspace and its four research workflows.
- [MCP for AI assistants](https://sunzu.com/for/ai-engineers/): supported research workflows, setup guidance and an assistant demo.
- [White papers](https://sunzu.com/papers/): original authored research. Full articles are open by default, with an optional PDF signup.
- [Methodology](https://sunzu.com/papers/2/): data enrichment, behavioural modelling, validation gates, traceability and research limitations.
- [Learn before you build](https://sunzu.com/papers/1/): practical guidance on testing decisions with AI simulations and evaluating business value.
Sunzu is AI user research software for product, design and marketing teams. Its composable AI combines 20+ layers, including algorithms and small models, to simulate human behaviour. Customer evidence grounds the research. Synthetic humans are AI simulations, not recruited participants; an audience models a customer group. See [product definitions](https://sunzu.com/research/#what-is-sunzu) and [method and validation](https://sunzu.com/research/#validation).
The web app supports depth interviews, concept testing, usability testing and ad testing. MCP supports depth interviews, concept tests and UX tests through compatible clients. See [research workflows](https://sunzu.com/research/#workflows) and the [MCP demo in Claude](https://sunzu.com/videos/mcp/). Audience findings complement research with real people; consequential decisions need human validation.
## Headline claims and their scope
Sunzu reports 96% of the insights humans can uncover and testing ideas, designs and ads 500× faster than human research. These are company-reported figures from internal research on proprietary data, concerning insight coverage and research speed respectively. Underlying datasets and detailed evaluation protocols are not published. They are separate from the study comparisons below and are not a guarantee for every study. See the [visible claim definitions and
…Machine-readable: GET /v1/resolve?q=sunzu.com · GET /v1/domain/sunzu.com · this page as Accept: application/json or text/markdown · MCP lookup_domain
Automatically discovered from public files. Inclusion does not imply endorsement or publisher participation.
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1. POST https://agentwebmap.com/v1/sites/sunzu.com/claims and keep claim_id and claim_secret private.
2. Publish the proof: add the line "AgentWebMap ownership: <token>" (token from step 1) to https://sunzu.com/llms.txt, or use the DNS, meta-tag or well-known method the response describes.
3. POST https://agentwebmap.com/v1/sites/sunzu.com/verify with {"claim_id": "...", "claim_secret": "..."}.
4. Save the api_key from the answer; it manages the listing (PATCH https://agentwebmap.com/v1/sites/sunzu.com).
MCP equivalent: tools begin_ownership_claim, then verify_domain, at https://agentwebmap.com/mcp. Docs: https://agentwebmap.com/docs#verifyCorrections or removal requests: contact the directory.