The dirty secret of AI asset production is the review pile. Generation is fast, but someone still has to open every output, catch the hand with six fingers, notice the missing logo, spot the drift from the brand — and the bigger your batches, the more that manual pass becomes the bottleneck. Volume was supposed to be the win, and instead it became the problem.
QA Outputs puts a number on it. Define what "on brand" and "good enough" mean for a title once, and Layer scores every generation against those rules automatically as it lands — brand adherence and overall quality, on the output itself. Review stops being a hunt through a thousand files and starts as a sort.
Key Capabilities
Brand adherence scoring Every output is checked against your brand as you have already defined it — the characters, palette, logo treatment and copy rules in your Projects and Reference Sets — and scored on how well it holds to them. No second description of your brand to maintain.
Overall quality scoring Alongside brand fit, each output gets a quality score: the anatomy errors, mangled text, artefacts and compositional misses that make an asset unusable regardless of whether it is on brand.
Rules you write once Scoring runs off rules you define, per workspace and per title, so "on brand" means what your art director says it means rather than a generic model's opinion of good.
Automatic on every generation Nothing to trigger and no separate pass to remember. Outputs are scored as they land, whether they came from a prompt, a workflow or an agent run.
Sort, filter and gate on the score Because the score lives on the output, a batch arrives ordered. Pull the top of it, send the bottom back, and let the middle be where your reviewers actually spend their time.
Scores the agent can act on The Creative Agent reads the scores its own generations get, corrects the prompt, and regenerates what fell short — so the correction loop that used to need a human round-trip closes on its own.
How It Works
Define what good means Set your scoring rules for the workspace or the title. Your Projects and Reference Sets already carry the brand definition, so this is about thresholds and emphasis, not re-describing your game.
Generate as usual Prompt, run a workflow, or brief the agent. Nothing about your production changes — scoring happens to the output, not to your process.
Review from the top Each asset carries its brand and quality scores. Sort by them, filter the failures out, and spend review time on judgment calls instead of defect-hunting.
Built for Game Production
Batches that stay reviewable A live-ops calendar or a UA test matrix means hundreds of outputs at a time. Scoring is what keeps a batch that size something a team can act on rather than something it dreads.
Brand consistency across a live title Months of content from many hands drifts. A score on every asset makes that drift visible while it is still one asset, not a season.
Ad creative with hard requirements Campaign creative comes with mandated elements and formats. Scoring against your own rules catches the misses that would otherwise cost a resubmission.
Fewer Creative Units on unusable output Consumption-based pricing means you pay to generate whether the result ships or not. Grading every output — and letting the agent retry the failures — puts more of that spend into assets that ship.
QA Outputs is what makes volume safe: the difference between a pipeline that produces a lot and one you can trust at scale, for the 400+ game studios and entertainment brands building on Layer.