Rivac LabsInclusive Visuals Specialist
AI image and video models carry the biases of their training data by default — narrow body types, skewed skin-tone distributions, stereotyped roles — and that shows up in brand imagery whether anyone intended it or not. This service audits generated and planned visual content for those patterns and corrects them through targeted prompting, generation settings, and sourcing, so imagery actually reflects the audience it's meant to reach. It's for teams scaling AI-generated visuals fast enough that nobody's individually reviewing every image for representation, and who don't want to find out about a bias problem from a public callout. The output is corrected assets plus a checklist your team can run without a specialist next time.
How We’d Approach This
A clear, staged plan — not a black box
- 1
Diagnose current or planned imagery for representation gaps and recurring bias patterns
- 2
Pilot corrected prompts and generation settings on a sample set to prove the fix works
- 3
Review results against inclusion criteria with stakeholders before applying it at scale
- 4
Build the corrected asset library and launch a reusable review checklist for ongoing content
What You Get
Deliverables from this engagement
- Representation audit report with specific findings
- Corrected image and video assets
- Inclusive-prompting guidelines for your team
- Reviewer checklist for future generations
- Ongoing spot-check process recommendation
Six Ways We Could Architect This
Different engagement, different build — pick the shape that fits
There’s more than one way to deliver on this service. Browse a few of the ways we’d structure the work, depending on your speed, budget, and integration needs.
Ready to get started?
Tell us what you’re trying to get done and we’ll help you find the highest-leverage place to start — scoped small enough to prove itself before you commit to anything bigger.
Talk to us about Inclusive Visuals Specialist