Understand the need
Capture use case, constraints and budget from the conversation itself, not from keyword matches.
DISCOVERY THAT ENDS IN ACTION
Make every recommendation shoppable.
Customers describe needs, not SKUs, and they increasingly describe them to an AI agent. AEL, the Agentic Engagement Layer, gives that agent live access to your catalog, stock and checkout, so the moment you're recommended is the moment you can be bought.
CUSTOMER INTENT→TRUSTED CONTEXT→ADAPTIVE EXPERIENCE→MEANINGFUL ACTION
01 / THE OPPORTUNITY
Checkout is moving into the conversation.
Assistants no longer stop at advice. They compare products, fill carts and increasingly complete purchases without opening a website. An agent recommends what it can verify and buys where it can transact. A store it can't read is a store it quietly skips.
02 / USER + CUSTOMER FLOW
Match against reality
Answer from live catalog, price and stock, so nothing gets recommended that can't be bought right now.
Close in one motion
Build the cart in the conversation and hand off to your checkout with everything attached, or complete it agent-side where you allow it.
WHAT CHANGES
Better journeys.
Measurable outcomes.
01Agent traffic converts02Carts survive the handoff03Attribution from day one
Be the store the agent can actually buy from.
Book a working demo ↗FAQ / E‑COMMERCE QUESTIONS
What teams ask about 42A for E‑commerce.
Clear answers about how 42A connects context, systems and customer action.
Customers describe needs, not SKUs, and they increasingly describe them to an AI agent. AEL, the Agentic Engagement Layer, gives that agent live access to your catalog, stock and checkout, so the moment you're recommended is the moment you can be bought.