
Profound
AI marketing platform for brands.

Pinterest Visual Search
Google Lens
Your own private collection. Discover fashion. Identify what you love. Your favorite stores in your pocket. Point your camera and discover new products.
Which is more popular?
Website, pricing, platforms and company facts side by side.
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| Website | digraph.dev | vant.style |
| Pricing | ||
| Company | Startup from the United States · 1 - 9 employees | 2026 |
| Listed in |
In their own words, as submitted to SaaSHub.


Digraph is an AI marketing platform for brands. It brings together AI research, market intelligence, website and campaign analysis, specialist AI workflows, and marketer-led guidance to help teams understand what shapes buyer decisions and what to do next. Teams can measure how AI systems...
VANT Style Concierge is a native iOS app that reimagines how people discover and shop fashion. Think of it as an iTunes Music Store for fashion brands: instead of scattering your favorite stores across dozens of bookmarks and apps, VANT brings your personal shopping world into one curated space....
What each product offers, as listed by its team.


Walkthroughs and reviews on video.
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Product CEMO
How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing Digraph.dev and VANT.style.
VANT.style's answer:
VANT combines three ways to discover fashion in one native app: a camera tool (Lens) that identifies clothing and products from any photo, a curated directory of brands (Mall) organized around personal style preferences, and an AI stylist (Style Chat) that gives real outfit advice pulled from an actual shoppable brand catalog. Instead of separate apps for inspiration, search, and shopping, VANT merges all three into a single experience.
VANT.style's answer:
Unlike general visual search tools like Google Lens or Pinterest, which surface generic web results, VANT is purpose-built for fashion and shopping. Every product identified through Lens links directly to a curated network of real retail partners, and the AI concierge only recommends brands that are actually in VANT's catalog — so every suggestion is something the user can buy.
VANT.style's answer:
Fashion-conscious shoppers, primarily women, who want a faster and more personal way to discover and shop for clothing, accessories, and lifestyle products than scrolling social media or browsing dozens of retailer apps individually.
VANT.style's answer:
VANT was created by solo founder Andrés Alecina, who taught himself to build the app with no prior coding background using Lovable, Supabase, and Xcode. Frustrated by how scattered and impersonal fashion discovery had become — spread across social media, retailer apps, and endless browser tabs — he set out to build a single native app that could identify, curate, and shop fashion in one place.
VANT.style's answer:
Built natively for iOS using Swift and Xcode, with a Lovable frontend, Supabase for backend and database, and OpenAI's GPT-4o and GPT-4o-mini models powering the AI style concierge and camera-based product recognition.
VANT.style's answer:
VANT is in its early growth stage, having recently launched on the Apple App Store. Our early adopters are fashion-conscious individual shoppers rather than named organizational customers — the app is built for consumers, not businesses. As we grow, we're also building a network of affiliate brand partners across major platforms like Awin, Rakuten, and CJ Affiliate, who benefit from VANT's curated in-app storefronts.
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