How Alokai Uses AI in the Storefront

Alokai applies AI on two sides of the storefront: behind it, where developers describe a change in natural language and AI builds it into the storefront (Studio), and in front of it, where shoppers describe what they need and get help from search through checkout (Compass). Both sit inside the same frontend platform that also includes the storefront itself, a data layer, cloud hosting, monitoring, and integrations. This applies if you run composable commerce on an existing backend stack and want AI applied to both building and buying, rather than as a standalone chatbot bolted onto the storefront.

The two AI surfaces, and who each one serves

Alokai's own framing is that "your developers build with AI, and your shoppers buy with it." That split is the clearest way to understand where AI actually sits in the storefront.

The distinction matters because the two solve different problems. Studio targets the "every change takes months" complaint — the gap between deciding on a storefront change and shipping it. Compass targets the shopper-facing side, where AI is meant to help people find and buy the right thing.

Studio: AI that builds the storefront

Studio is described as the component where "your team describes a change, AI builds it into the storefront." The input is a natural-language description of the change; the output is that change built into the storefront, with the platform's stated intent that it lands "to enterprise standards."

A concrete example of the kind of task this covers: adding a product slider to a page. Instead of a developer hand-writing the component, wiring it to the data layer, and pushing it through review, the team describes the slider and AI produces it. Alokai's own illustration shows this as a change moving through checks and approval — "Add a product slider," "Checks passed," "Waiting for approval" — which suggests the AI output still passes through a review gate rather than shipping unreviewed.

That review step is the part worth planning around. If your team already has a code review or release process, Studio's output has to fit into it; the platform presents the change as something that gets checked and approved, not something that bypasses your controls.

Compass: AI that helps shoppers buy

Compass is described as "AI built into the storefront, from search to checkout." This is the shopper-facing surface: rather than a separate assistant, AI is embedded across the buying path, starting at search and extending through to checkout.

The intent behind it is conversion — Alokai lists "We want AI that actually increases conversion" as one of the three problems teams bring to it, and points to "real agentic commerce use cases" as the answer. So Compass is positioned as commerce AI inside the storefront experience, not general-purpose chat.

One illustration in Alokai's material shows a shopper-facing flow where a request like buying a gift resolves into compared product picks and an add-to-cart action — the shopper describes what they need, and the storefront returns a narrowed, actionable result. That is the shape of the experience: description in, product decision and cart action out.

How the AI pieces relate to the rest of the platform

Studio and Compass are not standalone products. They sit alongside the other components Alokai lists as one platform:

• Storefront — a complete storefront your team owns and scales
• Connect — one data layer for your backend, CMS, and search
• Cloud — managed infrastructure run by Alokai at a 99.9% SLA
• Console — every deploy and metric in one place
• Commerce Intelligence — finds where your storefront leaks revenue and hands you the fix

The practical consequence: Compass draws on the same data layer (Connect) that connects your backend, CMS, and search, and Studio's changes land in the storefront your team owns. Commerce Intelligence is a third, distinct AI-adjacent capability — it is diagnostic rather than generative, identifying revenue leaks and supplying the fix rather than building features or serving shoppers.

What to check before assuming a fit

• Backend stack. Alokai positions itself as working with "the tools you already run" and offers ready-made integrations with existing vendors, so the AI surfaces are meant to layer onto your current commerce backend rather than replace it.
• Review process. Studio produces changes that go through checks and approval, so confirm how that maps onto your existing release gates.
• Which problem you actually have. If the pain is slow shipping, Studio is the relevant surface; if it is conversion in the buying journey, Compass is; if it is not knowing where revenue leaks, Commerce Intelligence is. They are separate components with separate jobs.
• Commercial terms. Alokai's site has a pricing page, but the available material does not state prices, plan limits, or whether any component requires a demo or login. Treat those as things to confirm directly rather than assume.