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Valeria

Product · Valeria

The AI layer that helps your customer. And your P&L.

Valeria lives inside your e-commerce as an embedded chat. It talks to customers, searches your catalog, builds carts. Along the way, it keeps your objectives in mind: margin, stock rotation, private label.

The problem

Big catalog. Scattered margin. And no one walking the customer through it.

On a modern e-commerce, most products never get real visibility. Searches return long, context-less lists. High-margin items, private labels and fast-rotation stock stay on digital shelves. The customer finds something, or leaves. Your P&L takes what's left.

The idea

An AI layer that knows your catalog. And your objectives.

Valeria is an embeddable chat that sits inside your store. It replies to customers in natural language, searches your real catalog, suggests recipes, builds shopping lists, adds items to the cart. Behind the scenes it balances two things: what the customer needs now, and what your business needs to sell.

What Valeria is not

  • Not a generic customer-service chatbot
  • Not an LLM wrapper
  • Not a black-box recommender
  • Not a replacement for your store
A close-up of the Valeria chat widget.

01 · How it works

What happens when a customer talks to Valeria.

Five steps. Each one is inspectable. Each one can be switched off.

  1. 01

    Understand

    Who's on the other side?

    Query, category, cart in progress, history, conversation so far: Valeria builds a live picture of the customer. What they are buying, under what constraints, with what price sensitivity.

  2. 02

    Search

    Inside your catalog, never outside it.

    Valeria queries your real catalog, with proper filters on category, brand, price and availability. No hallucinations: every product surfaced actually exists in your store.

  3. 03

    Balance

    The customer on one side. Your business on the other.

    On top of search results, steering kicks in: margin, stock rotation, private label, expiry. The weights are yours to set, and every ranking choice is reconstructable after the fact.

  4. 04

    Reply

    In the format that fits the moment.

    A product gallery, a shopping list, a recipe with ingredients already linked, a cart ready to confirm. Valeria picks the format that matches what the customer is asking for.

  5. 05

    Learn

    Everything is logged. Everything feeds back.

    What was shown, what was picked, what was ignored. Signals feed back into forecasts, into ranker weights, and into the dashboard where your teams read and steer.

02 · How it plugs in

Three pieces. One on top, one below, one beside.

No heavy rewrite on your side. Valeria is engineered to attach to an existing store, not to become it.

  • The Valeria widget inside a storefront, on iPad.

    In the store

    Widget

    An embeddable chat widget that lives inside your store. Customers talk to Valeria while they browse. A dedicated adapter connects it to whichever e-commerce you run.

  • A glimpse of the Valeria backend codebase.

    Under the hood

    Core runtime

    Valeria's brain: agents, memory, catalog search, multi-objective ranker, end-to-end logging. Single-tenant deployment, cloud or on-premise.

  • Screenshot of the Valeria retailer portal on a Mac.

    Where your team works

    Retailer portal

    The panel for the people running the store. Set steering objectives, weight margins and stock, read metrics, compare experiments.

02b · Connectors

Engineered to plug into your store, whichever one you run.

We're building connectors for the most adopted e-commerce platforms, in Italy and worldwide. Same Valeria runtime, a dedicated adapter per stack.

In development
  • Shopify
  • WooCommerce
  • OpenCart
  • PrestaShop
  • Magento
  • BigCommerce
  • Salesforce CC
  • VTEX
  • Mirakl
  • commercetools
  • Alokai

Don't see your stack? The runtime is platform-agnostic: tell us which one you run and we'll talk about a custom adapter.

03 · Outcome

What changes when Valeria is on.

Incremental margin per session versus a store without Valeria. Everything else is instrumental to that one.

  • North Star

    Margin / session

    Incremental margin per session, measured against a version of your store without Valeria running.

  • Session quality

    Conversion · spend

    Conversion rate and average spend per session: the leading indicators that tell us the assistant is helping the customer, not getting in the way.

  • Catalog health

    Stock rotation

    Private label surfaced, near-expiry moved, high-availability prioritised: the operational metrics that protect the P&L.

Want to see it inside your store?

Show us five representative products and your commercial goals. In thirty minutes we'll tell you if it's a fit, and how we'd approach it.