How I built a conversational commerce AI agent for a multimillion dollar e-commerce brand in 1 month

With so many variants of specialized products, buyers often struggle to decide, and the support team must always guide them through the process.

The client wanted an AI agent that could engage customers in natural conversations, understand their preferences, and recommend products accordingly. The goal was to enhance user experience, increase conversion rates, and reduce the workload on human support agents while also giving the support team full oversight and control over the agent's behavior.

// Solution

I built an AI agent that:

• - Helps customers find and select products
• - Recommends items based on preferences and context
• - Answers questions and completes tasks on behalf of users
• - Works seamlessly with the support team and hands off complex sessions to the right teammate

At the core, I engineered a context engine that proactively takes actions based on user needs, not just explicit requests. For example, if a customer raises an issue about a neglected ticket, the agent can automatically escalate it to higher priority without waiting for the customer to intervene.

The agent integrates directly into the client’s existing communications workflow, primarily powered by Zendesk, acting like an additional teammate; sharing key insights, notifying the right staff, and ensuring a smooth, coordinated support experience.

// The Impact

Customer satisfaction and support quality saw a significant boost. The workload for support staff decreased dramatically as routine guidance and handholding requests were handled autonomously. Time-to-purchase for customers dropped noticeably, as the agent reduced friction in product discovery and streamlined the buying journey.