AI Shopping Assistant That Truly Understands Needs

Increase conversions and build loyalty with personalized recommendations and expert guidance.

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Features

Transforming the Online Shopping Experience

Today's online shoppers crave the personalized attention of a physical store. They want expert guidance, not just endless product listings. Our AI shopping assistant helps you deliver exactly that.

Effortless Product Discovery

Guide customers to the perfect items based on their unique needs.

Personalized Recommendations

Increase average order value with AI-powered suggestions.

Instant Support

Provide immediate answers to customer questions, 24/7.

Conversational Engagement

Create a more enjoyable and personalized shopping journey.

How it works

Inside the AI-Powered Journey

Instead of relying on rigid keyword matching, the core AI analyzes the semantic meaning behind conversational queries like "find me a reliable coffee machine for a small office under €500." It identifies key attributes such as budget, usage context, and specific feature requirements simultaneously. This ensures the assistant understands the "why" behind the search, not just the "what," right from the first interaction.

Once the user's needs are understood, Vinder leverages direct API integrations to search through vast product catalogs in milliseconds. It filters out out-of-stock items and verifies current pricing to ensure all suggestions are actionable and accurate. This broad yet fast retrieval process guarantees that users are presented with the best available options that match their specific criteria.

Vinder goes beyond generic search results by applying a personalization layer that considers the user's past browsing behavior, brand affinities, and purchase history. The AI predicts which items the specific user is most likely to appreciate, weighing factors like style, sustainability ratings, or delivery speed. This results in a curated shortlist that feels like a recommendation from a knowledgeable friend rather than a database dump.

Users can ask follow-up questions, request side-by-side feature comparisons, or ask for summaries of pros and cons without leaving the chat interface. Vinder acts as a consultative sales associate, adjusting its recommendations in real-time as the user provides feedback or changes their mind. This conversational loop reduces decision fatigue and helps users feel confident in their final selection.

After a decision is made, Vinder facilitates the transaction by directly linking to the retailer's checkout page or processing the order within the assistant interface where supported. It can also auto-fill shipping details and apply known discount codes to maximize convenience and savings. This frictionless handoff minimizes cart abandonment and ensures a smooth conclusion to the shopping journey.

Frequently asked questions

Everything you need to know about Vinder. Can't find what you're looking for? Schedule a demo with our team.

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A: Integration is designed to be "plug-and-play" for major platforms like Shopify, Magento, and WooCommerce. We provide a lightweight JavaScript snippet that you simply drop into your site’s header. For custom-built stacks, our API documentation allows your dev team to connect your product catalog and inventory feeds in less than a day, ensuring Vinder is synced with your stock levels in real-time.

A: Absolutely. Vinder operates within strict "guardrails" that you define. It pulls information only from your approved product descriptions, policies, and active promotional data. It is explicitly programmed not to invent prices or promise discounts that aren't currently active in your system, ensuring all responses are brand-safe and factually accurate.

A: Vinder utilizes session data and purchase history (for logged-in users) to tailor recommendations. For a returning customer, it might suggest accessories for a previously bought item or restock consumables. For new visitors, it acts as a concierge, asking qualifying questions to narrow down their intent quickly. In both cases, the goal is to reduce search time and increase average order value (AOV).

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