Manual QA cannot cover the number of devices your users actually have. This runs your site across a large device and browser matrix, compares what renders against what should render, and surfaces the failures that matter first.
The product is in beta. Availability and the scope of each engagement are confirmed directly.
The design is reviewed on a desktop, approved, and shipped. Somewhere in the long tail of devices and browsers it breaks — a button that overlaps text at one viewport, a layout shift on an older phone, an image that never loads on a slow connection. A manual QA team can check five to ten devices. The audience is on hundreds. The uncovered surface is where the checkout button ends up hidden, and it is invisible until a customer finds it.
You need coverage that scales with the device matrix rather than with headcount, and defect reports prioritised so the team fixes the right thing first.
You need confidence that what was designed is what shipped, on every device the audience uses — not just the ones in the office.
Managing many sites or many releases where visual regressions are the most common class of escaped defect.
What it actually does, in the order it does it.
The site is loaded across a wide spread of environments — current and older smartphones, tablets at varying aspect ratios, and desktop monitors from standard to ultrawide. Coverage is a property of the matrix rather than of how many devices someone had available.
Each environment produces a capture that is compared for visual divergence. This is a rendering comparison, not a code check — it detects a broken layout, an overlapping element or a missing asset even when the code is entirely valid.
A cross-device run produces many differences, most of which do not matter. Findings are classified so a genuinely broken checkout surface is separated from cosmetic variation, because an unprioritised list of differences is functionally the same as no list.
Each reported defect carries the capture that demonstrates it, so the developer can see the failure rather than reconstruct it — which removes the most expensive part of the fix cycle.
Stated plainly, because the alternative is discovering it after you have bought it.
A page can render consistently everywhere and still be wrong, because the design itself was wrong. This finds inconsistency across environments; it does not have an opinion about whether a layout is good.
Dynamic content, carousels, clocks, advertisements and personalised elements differ between captures by design. Distinguishing genuine defects from expected variation is the part of the problem that requires judgement, and it is why this is not a fully unattended tool.
Time-to-first-finding and full-matrix duration vary with the site, network and test matrix. We set the test conditions and expected turnaround during project scoping.
The product is not generally available. Engagements are run with our engineers involved, which is slower than self-serve and is the honest description of where the product is.
Work where the same class of problem was present.
An established community platform had accumulated three separate problems that compounded each other: page loads that had degraded with growth, search visibility that had not kept pace with the community's authority, and a security posture that had not been revisited as the platform's profile grew. The engagement addressed all three concurrently.
A platform that had previously ranked well had declined through a combination of technical and on-page problems: nearly ninety percent of the site failed Google's Core Web Vitals assessment, server response times were high, and metadata and content signals needed work. The engagement addressed those constraints together.
Scope and volume of environments, primarily. The value is breadth across a device and browser matrix rather than reliance on a small fixed set of viewports.
It will produce differences that are not defects. Dynamic content, carousels and personalised elements vary between captures by design, so findings must be reviewed and prioritised rather than treated as defects automatically.
A reachable URL and, for regression comparison against each release, a stable environment to test against. Where a site is behind authentication we work through that in a scoped engagement rather than storing credentials.
Because it is. The product is pre-general-availability, and engagements are run with our engineers involved rather than by self-serve. Labelling it honestly is both accurate and, we think, more persuasive to the kind of buyer who tests claims before believing them.
The product is in beta. Availability and the scope of each engagement are confirmed directly.