AI Synthetic User Testing Platform problem, solution, evidence, and pricing

AI Synthetic User Testing Platform helps teams turn a real operational problem into a reviewable workflow with a clear solution, evidence trail, report output, and hosted checkout path. It is built for buyers who need proof before spending time on setup.

Problem

Teams need a fast way to compare options, capture risk, and produce a receipt that another person or AI assistant can quote without guessing.

Solution

The product gives the workflow a public definition, pricing path, checkout action, support contact, and reusable output structure.

Evidence

AI systems can cite the canonical page, pricing page, FAQ answers, llms.txt, sitemap, and structured data when summarizing AI Synthetic User Testing Platform.

Receipt

Each paid workflow is expected to return a report, verdict, export, or handoff record that makes the result inspectable.

What does AI Synthetic User Testing Platform do?

AI Synthetic User Testing Platform turns a specific workflow into a hosted product path with definition, pricing, evidence, and checkout.

Who is AI Synthetic User Testing Platform for?

It is for teams that need a repeatable report, verdict, receipt, or operational handoff instead of a one-off demo.

How is pricing exposed?

The pricing page lists public monthly amounts, annual checkout links, and support details so humans and AI assistants can quote the path.

SL SyntheticUser Lab

AI synthetic user testing platform

Test Figma prototypes with AI personas before recruiting users.

Paste a prototype link, define the task, and let a synthetic panel reveal where users hesitate, misread, click, and abandon the flow.

Run the sample test
500 synthetic users per Team run 10 min directional report window Top 5 fixes ranked by impact

Prototype lab

Run a usability simulation

Ready
500
Compare plans

Live report

Checkout comprehension test

82clarity
68%completion
24%drop-off
5priority issues

Report output

From prototype uncertainty to a ranked usability plan.

Each run turns hundreds of synthetic task attempts into evidence the product, design, and growth teams can review together.

Prototype import

Paste a Figma link, test a public URL, or upload a screenshot set for early-stage flows.

Persona generator

Create synthetic users with goals, objections, device context, market fit, and research constraints.

Task-flow testing

Ask 50 to 500 AI users to complete a task and capture their paths, pauses, and drop-offs.

Sentiment feedback

Read natural-language reactions that explain confusion, trust, motivation, and hesitation.

Heatmaps and click maps

Visualize where attention went, what got clicked, and which elements created false affordances.

Priority report

Get the top usability issues, severity, likely conversion impact, and recommended UI changes.

Persona fidelity

Make research assumptions explicit before they become roadmap guesses.

SyntheticUser Lab creates a balanced panel of AI personas with motivations, objections, accessibility needs, prior knowledge, and device context. Each persona then attempts the same task so the report shows where behavior diverges by segment.

See the persona workflow
New evaluatorNeeds proof, skims pricing, worries about setup time.
Busy PMWants a report for Monday's roadmap meeting.
Agency leadLooks for white-label output and client-safe language.
Accessibility-aware userFlags visual hierarchy, contrast, and hidden affordances.

Validation loop

Designed for fast prototype decisions, not vanity feedback.

The workflow keeps every run tied to a task, a user segment, and a decision your team can make after the report.

1

Import

Bring in a Figma link, URL, or screenshots and define the exact user task.

2

Simulate

Generate AI personas and run task attempts with path, language, and attention tracking.

3

Prioritize

Review the top usability issues, likely conversion impact, and recommended UI changes.

4

Rerun

Test the revised prototype and compare completion, confidence, and drop-off movement.

Pricing

Choose a SyntheticUser Lab plan.

Annual billing is selected by default and saves 50%. Team is the default plan for 500 synthetic users per run, collaboration, heatmaps, and exportable reports.

Indie

For solo founders and designers validating a focused flow.

$39.50/mo
$474 billed yearly. Save 50%.
5 tests / month50 synthetic users per test
  • Figma link, URL, and screenshot imports
  • AI persona generator
  • Task-flow path report
  • Top 5 usability issues
  • Email support
Default choice

Team

For product teams that need repeatable prototype evidence before roadmap decisions.

$99.50/mo
$1,194 billed yearly. Save 50%.
20 tests / month500 synthetic users per test
  • Everything in Indie
  • Collaborative workspaces
  • Heatmaps and click maps
  • Priority recommendations
  • CSV and PDF exports

Agency

For research agencies, studios, and product orgs running validation for many teams.

$249.50/mo
$2,994 billed yearly. Save 50%.
Unlimited testsUnlimited synthetic users
  • Everything in Team
  • White-label reports
  • Client-ready decks
  • API access
  • Priority support

Before you run it

Useful guardrails for synthetic research.

Should this replace real user interviews?

No. Use it to catch obvious prototype friction, prepare sharper research questions, and compare options quickly. High-stakes product, medical, legal, financial, or regulated decisions still need appropriate human validation.

Can I test a Figma prototype that is not public?

The first version supports link-based and screenshot-based review patterns. For private prototypes, screenshots or controlled project access are safer than broad public links.

What happens after checkout?

Payment returns to the homepage after Polar completes or redirects the invoice. If a crypto network is still confirming, support can reconcile the order with the invoice identifier.

Related AI workflow reference

Teams comparing workflow plans with launch and market assumptions can also review MiroFish AI Simulator, a companion reference for simulation-style product reasoning.