
Synthetic usability evidence workbench
Reduce reliance on live participants for early usability checks while keeping evidence and human review.
- For
- Product designers and UX researchers running quick usability checks on designs and prototypes
- Solves
- Live usability tests are slow and costly, so teams ship designs with unverified usability issues.
- Delivers
- Reviewed usability findings linked to design evidence
- Built in
- about 5 weeks of creation time, MVP in 6 days
- Investment
- $14,000 for the MVP, $47,500 for the full product
- Run it
- Inside your business, or as part of your offer to clients
What it does
Reduce reliance on live participants for early usability checks while keeping evidence and human review.
- Import Figma designs, prototypes and live URLs.
- Generate target user personas from transcripts or text descriptions.
- Run AI-simulated usability tests with synthetic users.
- Simulate think-aloud verbalizations during task completion.
- Capture transcripts and recordings of synthetic sessions.
- Predict attention with heatmaps and numeric clarity scores.
- Detect cognitive load and confusion points.
- Validate user flows with synthetic participants.
- Run multiple quick iterative test cycles.
- Compare design variations side by side.
- Surface accessibility and inclusive design issues.
- Consolidate findings from multiple synthetic participants into one report.
- Generate actionable design recommendations.
- Support multi-language test sessions.
- Capture reviewer corrections and named-owner approval before consequential use.
- Export a versioned reviewed usability findings report with source references and unresolved questions.
Everything these tools do, in one app
- AI-simulated user testing Runs usability tests with AI-generated users instead of live participants.Found in Snap, Uxia, Userology AI
- Fast feedback in minutes Delivers test results and summaries within minutes.Found in Snap, Uxia
- Figma plugin support Lets you run tests directly on Figma designs via a plugin.Found in Snap, Userology AI, Visual Usability Checker
- Test prototypes and live URLs Allows testing of interactive prototypes and live websites.Found in Snap, Userology AI
- AI persona generation Creates target user personas from interview transcripts or text descriptions.Found in Snap
- Think-aloud sessions Simulates users verbalizing their thoughts while completing tasks.Found in Snap
- Transcripts and recordings Provides written transcripts and recorded interactions from test sessions.Found in Snap
- Consolidated reports Combines findings from multiple AI participants into one report.Found in Snap
- Actionable recommendations Offers specific suggestions to improve the design based on test results.Found in Snap, Userology AI
- Instant flow validation Quickly validates user flows with synthetic users.Found in Uxia
- Iterative test cycles Enables running multiple quick tests to support iterative design.Found in Uxia
- End-to-end research workflow Automates recruitment, moderation, and synthesis in one flow.Found in Userology AI
- Screen-aware moderation AI interviewer watches the participant's screen and asks follow-up questions.Found in Userology AI
- Respondent pool and filters Access to a large opt-in panel with demographic and role filters.Found in Userology AI
- Multi-language support Supports testing in many languages.Found in Userology AI
- Accessibility checks Surfaces accessibility and inclusive design issues early.Found in Userology AI
- Attention prediction Predicts where users will look using eye-tracking data.Found in Visual Usability Checker
- Cognitive load detection Highlights areas that may confuse or slow users.Found in Visual Usability Checker
- Attention maps and scores Provides heatmaps and numeric scores to quantify visual clarity.Found in Visual Usability Checker
- Design variation comparison Compares design variations side-by-side to see how changes affect attention.Found in Visual Usability Checker
What goes in, what comes out
- Figma files
- Interactive prototypes
- Live URLs
- Persona descriptions or interview transcripts
- Task definitions
- Design constraints
AI drafts, people review. Evidence-backed analysis and reporting workspace.
- Reviewed usability findings linked to design evidence
How it works
The workflow
- InStart with
Figma files, interactive prototypes, live URLs, persona descriptions or interview transcripts, task definitions and design constraints
- 1
Confirm the buyer's problem and scope
- 2
Collect Figma files
- 3
Prototypes
- 4
Live URLs and persona descriptions
- 5
Then follow this sequence: 1
- OutFinish with
Reviewed usability findings linked to design evidence
AI does the heavy lifting, people stay in charge
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. Synthetic participants are not real users; findings require human review before design decisions. A model suggestion is never a verified fact, professional decision or authorization to act.
What your team sees
Primary screens: Study setup and persona selection, Synthetic session runner, Findings and recommendations. Use a thumbnail gallery for studies, a large central canvas for design preview and session playback, and a right-hand panel for findings, severity and comments. Let users compare design variations side by side. Display draft, in review and approved states. Provide a client preview link with comments anchored to the relevant screen. Make the task-specific outcome reviewed usability findings linked to design evidence visible beside its evidence, review state and value baseline.
Accounts and administration
Project ownership, design versions, reviewer comments, approval states, usage allowances, test limits, download history and a rights record for supplied material. Add organization access boundaries, named reviewers, usage caps, data retention controls, export logs and explicit approval for external actions.
Integrations and data access
Figma, prototype tools, live website URLs and design file storage. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
How we build it
We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.
- 1
Scoping call
Day 1Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.
- 2
MVP
6 daysOne buyer segment, one recurring use case; first modules: import Figma designs, prototypes and live URLs; generate target user personas from transcripts or text descriptions. Manual review in the loop. Built by our AI software factory.
- 3
Paid pilot
7 daysAccounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.
- 4
Full product
2 weeksSelf-serve onboarding, billing, monitoring and the wider integration set.
- 5
Run and improve
MonthlyWe host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.
Why we start with an MVP
An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.
- Pick the riskiest assumption. Here: will product designers and UX researchers running quick usability checks on designs and prototypes use it to solve "live usability tests are slow and costly, so teams ship designs with unverified usability issues"?
- Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
- Run a paid pilot. Agree quality and outcome thresholds before the pilot using this measure: Accepted usability findings per design iteration and reduction in unaddressed issues after review.
- Measure, then decide. Track accepted usability findings per design iteration and reduction in unaddressed issues after review; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase. Then expand, change course or stop, with evidence instead of opinions.
MVP scope for this solution. Pilot scope: One design tool integration (Figma), one prototype format and one live URL type; synthetic findings remain advisory and require human review. Implement one approved input format, a bounded representative case set and the first two task modules: import Figma designs, prototypes and live URLs; generate target user personas from transcripts or text descriptions. Support the remaining modules with operator review: run AI-simulated usability tests with synthetic users; simulate think-aloud verbalizations; capture transcripts and recordings; predict attention; detect cognitive load; validate user flows; run iterative cycles; compare design variations; surface accessibility issues; consolidate findings; generate recommendations; support multi-language sessions. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.
After the MVP. Once paid pilots prove usefulness, automate repeatable reviewed steps and add one verified source integration. Expand supported inputs and case volume only after new evaluation cases pass. Build reusable customer configurations and recurring value reports around reviewed usability findings linked to design evidence. Retain the explicit scope boundary: One design tool integration (Figma), one prototype format and one live URL type; synthetic findings remain advisory and require human review.
What the build depends on. Design upload and preview, asynchronous generation jobs, editable version history, reviewer access and tested export formats. High-fidelity usability requires specialist review. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One design tool integration (Figma), one prototype format and one live URL type; synthetic findings remain advisory and require human review.
Investment
A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.
- Phase 1
MVP
One buyer segment, one recurring use case; first modules: import Figma designs, prototypes and live URLs; generate target user personas from transcripts or text descriptions. Manual review in the loop.
- Phase 2
Paid pilot
Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.
- Phase 3
Full product
Self-serve onboarding, billing, monitoring and the wider integration set.
Indicative total, MVP to full product$47,500about 5 weeks of creation time · start with the MVP from $14,000
Running costs per month
A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.
| Stage | Hosting and infrastructure | AI usage | Total per month |
|---|---|---|---|
| MVP and paid pilotabout 3 customers | $30–$60 | $80–$160 | $110–$220 |
| Full productabout 50 customers | $110–$210 | $880–$1,750 | $990–$1,960 |
Run it or resell it
For your own team
Product designers and UX researchers running quick usability checks on designs and prototypes run it inside the business: figma files, interactive prototypes, live URLs, persona descriptions or interview transcripts, task definitions and design constraints in, reviewed usability findings linked to design evidence out, reviewed by your people.
As part of your offer
Agencies, consultancies and software companies can offer it to their own clients under their brand. We build and maintain it; you sell and deliver it.
Your brand, or this one
Run it under your own brand, or start from this concept style.
- primary
#6f2791 - accent
#87c954 - surface
#ede4f1 - ink
#22201e
- Headings
- Fraunces
- Text
- Inter
- Voice
- Curious, rigorous, user-led
Selling it to your own clients: the go-to-market playbook
Pricing to test
Test a USD 300-1,500 fixed pilot for one defined design package. Offer a monthly production allowance after repeat demand. Quote complex multi-language or accessibility certification separately. These are test prices, not market benchmarks. Package the initial sale as one bounded reviewed usability findings report. Recurring fees must specify volume, review depth and integration support. For exchanges, test a disclosed coordination or successful-service fee rather than holding customer funds. Reprice only after measuring real delivery labor; platform-build cost is separate from a commercial pilot fee.
Message to test
Reduce reliance on live participants for early usability checks while keeping evidence and human review. Demonstrate a concrete reviewed usability findings report using the buyer's approved example and show the baseline, corrections and actual delivery effort.
Where to find buyers
Product designers and UX researchers professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.
Lead magnet
A reviewed sample usability findings report from a small authorized design set, with a transparent calculation of accepted usability findings per design iteration and reduction in unaddressed issues after review and no promised savings.
The first 30 days
- Week 1: interview five product designers and UX researchers running quick usability checks on designs and prototypes and inspect a recent example of live usability tests being slow and costly, so teams ship designs with unverified usability issues.
- Week 2: prepare a consented or synthetic demonstration of the task modules.
- Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
- Week 4: measure accepted usability findings per design iteration and reduction in unaddressed issues after review, reviewer effort and repeat-purchase interest. This is a demand-validation plan, not a thirty-day full-product delivery promise.
Paid pilot
Agree quality and outcome thresholds before the pilot using this measure: Accepted usability findings per design iteration and reduction in unaddressed issues after review. Continue only if the buyer accepts the actual output, the intended job outcome improves without unacceptable errors, and measured delivery cost fits willingness to pay. Revise or stop if access is unavailable, qualified review cannot be provided, or apparent savings disappear after corrections and support. Use held-out cases when comparing model quality; use a properly reviewed comparison design before making causal claims. Record missing cases and negative results alongside successful outputs.
Success metrics
Accepted usability findings per design iteration and reduction in unaddressed issues after review; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.
Retention and expansion
Repeat the workflow when the buyer again needs reviewed usability findings linked to design evidence. Retain permissioned settings and reviewed examples, report realized value honestly, and sell increased volume or adjacent approved workflows only after contribution margin and quality remain acceptable.
Why clients would pick it
A reusable library of approved usability patterns, design constraints and review examples, together with reliable delivery for a narrow product design niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for product designers and UX researchers running quick usability checks on designs and prototypes. Repeatable delivery and useful integrations matter more than access to a base model.
Alternatives and positioning
Snap, Uxia, Userology AI and Visual Usability Checker, plus live usability testing services and generic design review tools. Compare this product with the buyer's present method on accepted usability findings per design iteration and reduction in unaddressed issues after review. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.
Main delivery costs
Synthetic session generation, storage, reviewer hours, client revision rounds and licensed source assets. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of reviewed usability findings linked to design evidence. Track cost per accepted output, including correction work, unsuccessful cases and support.
Safeguards
Preserve design intent, source attribution, quotation accuracy and usage permissions. Designers approve substantive changes and publication scope. One design tool integration (Figma), one prototype format and one live URL type; synthetic findings remain advisory and require human review. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.