World's Largest AI Native eB2B Retailer App

A traditional retailer ordering app is a digital order pad: the same catalogue for every store, search that requires the retailer to know what to look for, and promotions pushed on a calendar.
AI Native eB2B decides what each store should buy before the store opens the app. ML models read every past order — from that store and from comparable stores — and then:

Predict the next order

Build a ready-to-order basket shaped by the store's purchase patterns, size, and category mix

Surface products the store has never ordered but similar stores buy regularly

The difference is architectural. Because the intelligence core sits above business logic rather than beside it, personalization reaches the landing page, catalogue, search, and promotions — not just a recommended-products strip.
That shows up in the numbers: 15%–28% new SKUs per order, 8%–12% higher average order value, and 30%+ higher adoption and engagement.

It means every surface the retailer touches is built for that specific store — not personalized at the margin.

The landing page, catalogue, and search adapt to the store's purchase history

The basket opens ready to order, shaped by that store's patterns, size, and category mix

Order prediction runs before the retailer opens the app, and each line carries the distribution and revenue opportunity it represents — so a missed SKU has a visible value

Promotions, flash offers, and reorder nudges fire on store behavior rather than a campaign calendar

"100%" is a claim about coverage, and it holds only because personalization is computed in the platform's intelligence core and served to every layer above it. A recommendation engine bolted into an app personalizes one screen; an AI Native architecture personalizes the whole session — which is what drives 5%–18% higher focus-product distribution and 30%–50% higher engagement.

This is the question that decides eB2B, because most brand ordering apps are downloaded once and abandoned. The evidence here is public:

4.5 stars across 126K+ retailer reviews

1M+ downloads and 85+ deployments in 25+ countries

Against competing platforms averaging 3.5–4.0 stars

Retailers rate it that way because the app removes work rather than adding it — opening with a ready-to-order basket instead of an empty search bar — and because they can order through whichever channel suits them: voice, text, WhatsApp, PWA, or native app.
Sustained usage is what the impact numbers depend on. Among retailers placing 70%+ of their orders through the app, 90%+ show measurable uplift across order value, product discovery, and engagement. That's the honest way to state it: the platform earns its results from stores that actually adopt — and adoption is designed into how the ordering experience works.

No — and the architecture is the reason. eB2B, SFA, and DMS are compositions of the same micro-services on one data spine. An order placed by a retailer in the app enters the same order engine as one taken by a rep, and flows to the distributor through the same distribution management layer.
The channel doesn't fork, it widens. Reps keep their relationships and high-value calls; the app covers the reorders, the between-visit demand, and the stores a beat can't reach at economic frequency.
The same intelligence core serves everyone, which is what prevents conflict from becoming structural: retailer recommendations and rep recommendations come from one model — so the app isn't selling a different plan from the person standing in the store.