Agentic Commerce Visual Signal
The visual signal AI shopping agents are missing
As AI shopping agents increasingly evaluate or purchase on a shopper's behalf, structured product-feed data alone can't answer whether something actually suits a specific person. Gennoctua supplies that missing visual signal.
How it works
From install to live in about three days
- 1
Same underlying render
The identical Style, Fit & Match signal used in human-facing try-on is generated from the shopper's own body or space.
- 2
Expressed as structured signal
The verdict is expressed in a form an agent can act on with confidence — not just a human-facing visual UI.
- 3
Paired with product-feed data
Agentic commerce already relies on structured product feeds; Gennoctua supplies the visual complement those feeds are missing.
- 4
One signal, two audiences
The same underlying signal serves both the human shopper and the agent acting on their behalf — not a separate product.
Who this is for
Built for technical and product teams evaluating agentic commerce
This is the visual complement to structured data feeds specifically for agentic and AI-driven purchasing flows — an additional buyer (the agent) for the same underlying signal humans already see.
How Gennoctua actually handles a shopper's image
Consent and image capture happen directly inside the plugin, at the point of use. Generation is cloud-assisted today — on-device generation isn't yet mature enough to run at production quality, so we're honest about that rather than claim otherwise. The result is cached on the shopper's own device, not retained on Gennoctua's or the retailer's servers, and each install captures fresh rather than sharing an identity across apps.
FAQ
Frequently asked questions
What is a visual signal for agentic commerce?
It's a Style, Fit & Match verdict — grounded in an individual shopper's actual body or space — expressed in a structured form an AI shopping agent can act on, not just a human-facing visual interface.
Why isn't structured product data enough for AI shopping agents?
Structured product-feed data alone can't answer whether something actually suits a specific person — that requires a signal grounded in the individual, which is what Gennoctua's Style, Fit & Match render provides.
Does this replace the human-facing try-on experience?
No — it's an additional use of the same underlying signal, for a second audience (the agent) alongside the human shopper, not a replacement.
Who typically evaluates this use case?
Technical, product, and innovation-facing teams — CTOs, heads of AI or product, and innovation leads — more often than a pure marketing contact.
The other three use cases
Gennoctua also shows up as
Catalog-Wide Visual Try-On
Frictionless, secure "see yourself in it" across apparel & footwear, eyewear, jewelry & bags, and furniture & décor — confirmed by Style, Fit & Match signals before checkout.
Personalized Video at Scale
Each shopper becomes the actual subject of the product or ad video — not a model — generated per person, with no new shoot required for every SKU or audience segment.
Touchless In-Store Try-On
The same experience extends onto the retail floor — easing fitting-room congestion and letting associates support more shoppers at once, without adding headcount.
See it on your own catalog
Live in about three days, pay-as-you-go. Book a walkthrough built around your own products.
Book a demo