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AICap is the AI-driven engagement and merchandising platform for physical retail. Every shopper gets an on-demand product expert that knows their needs and your assortment, then helps them discover, compare, and decide. You get a measurable digital funnel from shopper intent to purchase.

You invest to get shoppers through the door. Then the decision path goes passive — the same shelves, signs, and promotions for everyone, and no record of what any shopper was actually trying to do. AICap makes that high-intent traffic responsive and measurable.

AICap holds more product knowledge than any associate can carry, never runs out of patience, and serves everyone at once. Shoppers who prefer to explore privately can ask anything without waiting or pressure, then bring in an associate when human help adds value.

Scan a QR code or tap a store screen, then speak, type, or touch. Say what you need — AICap narrows your assortment, compares the strongest options, explains the tradeoffs, answers follow-ups, and points to the shelf.

No. A scan opens AICap in the browser and the conversation starts immediately. The shopper gets personalized, store-specific help without stopping to install an app or create an account.

No. AICap runs on shopper phones and on screens you already have. Dedicated kiosks and tablets are available when a store wants a permanent aisle presence, but nothing is required to launch.

It creates more value from traffic already inside the store — saving uncertain purchases, improving mix, supporting trade-up and cross-sell, completing baskets, introducing unfamiliar products, and making promotions land with the right shopper. The target is gross-margin dollars, not clicks.

High conversion makes AICap more valuable, not less. The opportunity is what they buy: which brand, which price point, whether they trade up, whether they add the complementary item, whether uncertainty quietly shrinks the basket. AICap works on the decisions between the door and the register.

It doesn't. Availability is a hard constraint, not a ranking factor — out-of-stock products are excluded from recommendations. When a shopper wants something you don't stock, AICap tells you, which is often the more valuable signal.

It absorbs the knowledge-heavy part of selling — answering questions, explaining products, comparing options, qualifying needs. Your team spends more time on relationships, service, and judgment, and receives the shopper's need and shortlist when a handoff makes sense.

It combines what the shopper says with deep product knowledge and your actual assortment, then weighs fit, hard constraints, price, availability, store context, and your economics to produce a small set of strong choices — each with a reason attached.

Exact facts — product identity, price, availability, hard constraints — come from structured sources, not from a model's memory. Recommendations and explanations build on that foundation, so the shopper gets guidance grounded in facts.

The decision itself becomes visible: what shoppers are trying to accomplish, what they ask, what confuses them, what they compare, what they reject, what changes their mind, and what they buy. That reshapes assortment, merchandising, and promotion decisions.

You do, for your stores. Onki's business is influence and measurement, not selling identifiable shopper data — that isn't a policy we adopted, it's the model we built. Retailers get the shopper and session data they want to see.

In standard AICap, Onki manages brand participation and recommendation policy. Retailers wanting direct control over brands, campaigns, content, and policy use the retailer-controlled product. In both, brand participation works within shopper fit, product truth, availability, and your assortment.

Brands fund product education, offers, and measurable participation around live shopper decisions. You get a brand-funded engagement layer, shoppers get better guidance, and brands get a responsive, measurable channel during the active purchase decision.

It connects to catalog, pricing, inventory, promotions, POS, product location, loyalty, and ecommerce, so guidance reflects the real store and outcomes are measurable. Launch needs the catalog; everything else deepens the experience as you add it.

Yes — conversational, store-specific help across languages, which matters most in exactly the neighborhoods and categories where a shopper is least likely to ask an associate for help.

AICap creates the most value where choice is hard: large assortments, unfamiliar attributes, preference-driven decisions, real trade-up opportunity, and thin expert coverage. Onki starts with alcohol and is built to extend across physical retail.

AICap links shopper interactions to downstream actions and POS outcomes. Success is incremental gross-margin dollars; engagement, mix, basket, and conversion explain where the lift came from.

Very little. You provide the catalog and basic store information. Onki handles setup, configuration, and the shelf materials. Deeper integrations get added when they create more shopper or measurement value.

Standard AICap is free. Brand participation funds it. Retailers wanting control over content, recommendation policy, campaigns, integrations, reporting, or governance use the paid retailer-controlled product.

Yes — one store, one category, or one shopper use case. AICap measures engagement and economics inside a bounded deployment, then expands across stores, categories, and surfaces as results justify it.

On two clocks. Within a conversation, each answer sharpens the current recommendation. Across sessions and stores, outcome-linked interactions improve future recommendations, merchandising, campaigns, and measurement.