Agentic-Commerce Product Discovery & Reorder Chatbot

Overview

Agentic-Commerce Product Discovery & Reorder Chatbot is a no-code, white-label conversational agent built on NIVA's persona, flow, and smart-form engines. Shoppers increasingly research and select products through conversation rather than keyword search and category browsing, and brands that only expose a traditional storefront lose discovery to AI-driven channels. With NIVA, a retail persona indexes a clean product catalogue into a knowledge base and answers natural-language discovery queries (needs, constraints, comparisons), guides selection, and enables fast reorders by recalling past purchases via memory. A per-persona tool can check live price or stock, and a webhook pushes the cart or order. Note: this is a brand-owned conversational discovery layer, not an external agent-checkout protocol integration. The result is a measurable shift from manual, after-hours-limited handling to instant, structured, around-the-clock engagement that feeds directly into your systems.

The problem

Shoppers increasingly research and select products through conversation rather than keyword search and category browsing, and brands that only expose a traditional storefront lose discovery to AI-driven channels. For retail & e-commerce teams specifically, every hour spent on this manually is an hour not spent on higher-value work, and every unanswered query outside business hours is a lost opportunity that a competitor with instant response will capture.

How NIVA solves it

A retail persona indexes a clean product catalogue into a knowledge base and answers natural-language discovery queries (needs, constraints, comparisons), guides selection, and enables fast reorders by recalling past purchases via memory. A per-persona tool can check live price or stock, and a webhook pushes the cart or order. Note: this is a brand-owned conversational discovery layer, not an external agent-checkout protocol integration. Because the persona is pre-trained for retail & e-commerce and the logic is assembled in a no-code flow, the team owning this does not need engineering support to launch or iterate. Every conversation is logged and attributed, so the same deployment doubles as an insight layer revealing the questions and friction points worth acting on.

Automation flow

1. Trigger: a needs-based or comparison product query
2. Knowledge base: match products from the catalogue by criteria
3. API call: check live price and stock
4. Memory: surface past purchases for one-message reorder
5. Webhook: push the cart or order

Before vs after

How it works under the hood

Under the hood this maps to NIVA's documented engines. The persona engine handles tone and routing for retail & e-commerce, drawing on a library of pre-trained personas so the agent speaks the language of the domain from day one rather than being trained from scratch. The flow engine runs the conditional steps in the sequence shown above, branching on the visitor's answers so each person follows the path that fits their situation. The smart-form engine surfaces structured fields at the moment intent appears, capturing clean data inline instead of bouncing the user to a separate form. Cross-session memory preserves context so returning users are recognised and never asked to repeat themselves. Finally, webhooks push the completed interaction into your systems of record, and per-persona tool calls can read live data from your APIs mid-conversation wherever an endpoint exists. None of these steps requires writing code; they are assembled in the no-code admin and embedded with a single script tag.

Who this is for

This is a public-facing deployment that engages prospects and customers directly on your website or app. It is designed to capture demand that would otherwise be lost outside business hours, to deflect the repetitive questions that consume your retail & e-commerce team, and to turn anonymous traffic into structured, followed-up leads.