Use Case

Review Your Build Before Anyone Files Feedback

Catch visual issues before reviewers do. Compare your build against the approved design and export issues to Jira, Linear, or Notion. Every issue you catch internally is one fewer feedback ticket.

Two types of issues worth catching before your review round

What reviewers would catch: Wrong button colors, broken layouts, misaligned sections — a reviewer would spot these and file a ticket. When you review your own build against the approved design first, you find and fix these before the feedback round starts. According to Webvizio, 57% of creative teams need 3-5 revision rounds before approval. Catching the obvious issues internally cuts that cycle.

What nobody would catch: Spacing off by 4px. A font weight that is 100 too light. A gray that is close but not your brand color. No reviewer would file a ticket for these, but they compound into a build that feels slightly wrong without anyone being able to say why. AI and Visual Comparison catch this class of issue — the kind that no feedback loop ever surfaces.

Common problems OverlayQA solves

• Waiting for others to find your issues — Without a structured review of your own build, visual problems surface during feedback rounds instead of before them.
• Side-by-side eyeballing misses things — Comparing your build to a design in two windows catches the obvious problems but misses subtle spacing, color, and typography drift.
• Revision rounds compound — 57% of creative teams need 3-5 revision rounds before approval (Webvizio). Each round adds time because issues surface one at a time.
• No direct comparison to the approved design — Without comparing your build against the Figma design, you cannot verify that spacing, colors, fonts, and layout match what was approved.

How OverlayQA website review works

1. Open your build — Navigate to any page on staging or production where you want to review.
2. Load the approved Figma design — Connect your Figma frame to compare your build directly against the approved design.
3. Run AI Design Review — AI analyzes your build for visual issues — spacing, colors, fonts, layout — and flags problems with severity context.
4. Capture and document issues — Click any element to capture a screenshot and element context. AI drafts a structured issue description ready for export.
5. Export to your tracker — Send issues to Jira, Linear, or Notion. Developers get everything they need to fix without back-and-forth.

Frequently asked questions

Who is this for?

OverlayQA is built for design and development teams reviewing their own builds. Rather than waiting for a client or stakeholder to file vague feedback, you review your build against the approved Figma design before any feedback round begins. Every issue you catch internally is one fewer revision ticket.

What types of visual issues does OverlayQA catch?

Two types. First, the obvious mismatches — wrong colors, broken layouts, misaligned elements — that a reviewer would catch anyway. You find these first so they never reach a feedback ticket. Second, the subtle drift that nobody would notice by eye: spacing off by a few pixels, a font weight variation, a color that is close but not exact. AI Design Review surfaces these automatically.

How does Visual Comparison work for website review?

You connect your approved Figma frame to OverlayQA, then compare it directly against your live build. Visual Comparison shows you where colors, spacing, fonts, and layout have drifted from the approved design, without switching between windows or eyeballing manually.

How does reviewing your own build reduce revision rounds?

According to Webvizio, 57% of creative teams need 3-5 revision rounds before approval. When you catch obvious visual issues before a feedback round starts and fix them first, reviewers see fewer problems per pass. Agencies with structured review processes see 60% fewer revision rounds (DesignRush).

How does AI catch issues that manual review misses?

Human reviewers are reliable at spotting obvious problems but miss subtle drift — spacing inconsistencies of a few pixels, slight color variations, font weight differences. AI Design Review analyzes your build systematically and flags these issues with severity context, so you raise quality beyond what any feedback loop would surface.