In retail and e-commerce, customers are increasingly autonomous, but also increasingly hesitant. Too many choices, too much information, and too little personalized guidance.

In practice:

• Customers abandon their carts due to unanswered questions or lack of timely advice.
• Sales teams cannot support every visitor individually.
• Traditional tools rely on generic recommendations or static FAQs that fail to engage.

The result is a fragmented shopping experience, lost conversions, and limited differentiation in markets where competitors offer similar catalogs.

Yet customers expect a simple, fluid experience, similar to an in-store salesperson who understands their needs, recommends the right products, and reassures them at the right moment.

Understands purchase intent in natural language

The agent interacts with customers to identify needs, constraints, preferences, and purchase maturity.

Recontextualizes with available data

It leverages product catalogs, inventory, pricing, promotions, customer history, and browsing behavior to refine recommendations.

Delivers personalized recommendations

The agent suggests relevant products or options, explains differences, addresses objections, and provides reassurance.

Guides customers to action

It can direct customers to the right product, add items to the cart, suggest complementary products, or escalate to a human advisor when needed.

Ensures continuity with customer support

If the conversation shifts to post-purchase questions or support needs, full context is transferred seamlessly to customer service, with no journey break.