UX diagnosis based on observable evidence.
Know what to change, what to verify, and what not to decide yet. UXMachine retains each page’s history and learns from its evolution instead of starting from scratch.
No account required.
It remembers the page, unlike a generic AI wrapper
Most AI tools diagnose each screen from scratch and forget it once the chat ends. UXMachine keeps a dated, per-page memory: each new reading is compared with that page’s own history. Here, learning means building longitudinal, per-page memory — not retraining the base model or deriving global norms from other pages.
Current evidence always takes precedence over prior memory. What is UX Memory →
Real UX readings
See real examples →Independent readings of public pages. Not clients, endorsements or commissioned audits.
Webflow
Usable reading with caveatsThe hero's primary action reads more like a text link than a button.
Open reading →Two ways to read a UXMachine diagnosis
Start with the executive summary when you need a fast decision. Open the full report when you want to inspect the evidence.
Quick read · 3 minutes
Use the executive summary to understand what may be blocking clarity, trust or action — and what to review first.
Deep read · 20 minutes
Use the full report to inspect the visual and textual evidence behind the recommendation.
- URL or screenshot
- Visual + textual reading
- Friction signals
- Prioritized decision
- 3-minute summary / 20-minute report
From evidence to decision
Observable signal
The primary CTA competes with two actions of the same visual weight.
UXMachine interpretation
The main action is not identifiable at first glance.
First decision
Give one action clear visual priority; verify it against the screenshot before touching the rest.
Friction patterns vs clarity patterns
- Abstract promiseConcrete benefit
- Competing CTAsOne primary action
- Hidden social proofTrust before effort
- Claims without evidenceDemonstrable arguments
- Flat hierarchyGuided decision sequence
How it reads across pages
SaaS / startup landing
A product headline followed by a dense mockup: the main action gets buried. First decision: place one clear CTA next to the value proposition.
Campaign / lead-generation landing
An overlay interrupts the hero and competes with the form. First decision: free the CTA area before asking for data.
Services / education / consulting page
Logos and proof sit below the fold while the form asks for effort too early. First decision: move trust signals before the request.
URL, Capture and UX Memory
URL to start fast. Capture to review specific screens. UX Memory to accumulate evidence and see whether the product improves.
URL to start fast
Start with a public URL to get a first actionable UX reading.
Capture for specific screens
Upload a capture when you need to review a specific screen, private page, prototype or app state.
UX Memory to accumulate evidence
Save diagnostics in UX Memory to compare changes, accumulate evidence and understand whether the product is improving.
What you receive
What to change first
A prioritized decision with visible evidence and a confidence level — not a long generic report.
What not to touch yet
Signals without enough evidence to act on right now. Avoid changes that are not supported by what is observable.
What to verify before acting
The next concrete verification step to confirm or rule out the recommendation before redesigning.
How it works
- 1
Paste a URL
- 2
UXMachine captures and analyses the URL
- 3
You receive a diagnosis based on visible evidence
- 4
Create an account when you want memory, history and continuity
What visible evidence means
Visible evidence means what can actually be observed on the screen: copy, buttons, hierarchy, contrast, forms, navigation, calls to action and signals that may affect comprehension or conversion.
Why it is different
- Based on what is visible. The diagnosis starts from the first screen, not from generic UX advice.
- Recommended actions, not long reports. The output is designed to help you decide what to review first.
- Clear limits. When the evidence is not sufficient, UXMachine marks the signal as something to verify.
UXMachine uses AI to read the screen and organize visible signals, but it does not replace human judgment or full user research. Explore the evidence-first UX audit approach or see how cognitive friction appears on the first screen.
What it returns
UXMachine does not turn every observation into an alarm. It separates recommended actions, signals to verify and elements that are better left unchanged for now.
UXMachine does not replace Lighthouse. It complements it.
Lighthouse measures performance, SEO, technical accessibility and best practices. UXMachine helps interpret whether the first screen is clear, oriented and trustworthy.
One tells you whether the page meets technical checks. The other helps you decide what to review first from a UX perspective.
From one diagnosis to UX memory
Without an account, you can run a public diagnosis and see the result immediately. With an account, future diagnostics are saved so you can compare changes, build project memory and return to previous findings.
It remembers a page and learns from its evolution
UXMachine does not start every diagnosis from scratch. It retains previous observations of a page, compares each new reading with its history, and learns from that continuity to show what persists, what changed, and what still cannot be concluded.
Dated observation
Each reading is stored with a date, so a page has a record over time, not a single snapshot.
Longitudinal comparison
New readings are compared with earlier ones for the same page to see how it evolves.
Persistence, change and abstention
The report distinguishes what stays the same, what has changed, and what the evidence still cannot confirm.
Per-page learning
Learning here means building longitudinal, per-page memory — not retraining the base model or deriving global norms from other pages.
No comparative claims
UXMachine does not rank your page against brands, competitors or other AI models.
Current evidence always takes precedence over prior memory: the history adds context, it never replaces the present observation.
UXMachine gives you a fast, evidence-based first read of a page — it does not replace user research, and it says so when the evidence is not enough to decide. Read the limitations →
Start with one real landing
Try a public URL and see whether the first decision helps you prioritize what to change, what not to touch and what to verify.
Diagnose a URL →Frequently asked questions
- What does UXMachine analyse?
- The first visible view of a public URL — copy, hierarchy, CTAs, trust signals, contrast and cognitive friction patterns observable on screen.
- What do I receive?
- A prioritized decision (what to change first), signals to verify before acting, and a 'don't touch yet' track for elements without enough evidence to act on.
- What is the confidence level?
- High, medium or low — indicates how strongly the observable evidence supports each recommendation. Low confidence means the signal is present but needs verification before acting.
- What does 'don't touch yet' mean?
- A separate track for elements where the current evidence does not justify a change. It prevents acting on weak signals and is part of every analysis output.
- Does UXMachine replace user research?
- No. It gives you a fast, evidence-based first read of the first screen. It does not see analytics, session recordings or conversion data.
- Does it work for any type of website?
- It works best with public landing, product and service pages. It is not designed for authenticated app interiors, dashboards or multi-step flows.
- Can it tell me why my landing page is not converting?
- It can surface observable friction that may affect comprehension and conversion. It cannot diagnose causes that require analytics or qualitative data.
- Does UXMachine learn automatically?
- Yes, in a specific sense: it automatically builds longitudinal memory for each page, retaining dated observations and using previous readings to interpret how the page evolves. It does not learn across unrelated customers or derive global UX norms.
- Does UXMachine retrain the AI model?
- No. Learning here means building longitudinal, per-page memory and using previous observations to interpret how a page evolves — not retraining the base model, modifying its weights, or deriving global norms from other pages.
- What happens when current evidence contradicts the history?
- Current evidence always takes precedence. The history adds context and flags what changed, but it never overrides what is observable in the present reading.
About UXMachine
UXMachine is built around a simple idea: many UX audits produce too many recommendations and too few clear decisions.
We help founders, product teams and marketing leads read a page with sharper judgment: what is clear, what builds trust, what blocks action, and what should be reviewed first.
UXMachine combines automated reading, visual evidence and strategic judgment to turn a URL or screenshot into a more useful decision.
Read more about UXMachine →