StoreHippo has an AI commerce engine built directly into its core, so key AI features like semantic search, product recommendations, image enhancement through Magic Edit and AI-assisted catalogue creation come natively without any plugins. 

All AI features work out-of-the-box enabling brands to leverage them from day one. However, if your brand wants to build custom AI agents or advanced, business-specific AI workflows on top of the native capabilities, those are discussed separately and priced on a pro-rata basis depending on your use cases and scale.

StoreHippo’s built-in AI engine can automatically generate product listings for large inventories. For example, it can scan uploaded product images and data, then create clean, SEO-friendly titles, descriptions, categories and attribute mappings, without manual work. This makes the catalogue setup much faster when you have hundreds or thousands of products.

Yes, StoreHippo’s built-in AI image editor Magic Edit can automatically clean, enhance and resize product images. Magic Edit improves lighting, adjusts backgrounds and optimises size/format so product photos look consistent and professional without the need for manual editing.

StoreHippo’s AI feature for search uses semantic understanding instead of exact keywords, so it reads intent, context and synonyms to show the most relevant products instantly. This helps buyers navigate large or complex enterprise catalogues without confusion. The AI search engine also learns from each buyer behaviour and interactions and improves results over time, making product discovery faster, smoother and more accurate across enterprise B2B, B2C or multi-vendor marketplace setups.

Agentic AI assistants personalise buyer journeys by understanding each shopper’s intent, behaviour and past interactions. They adapt recommendations in real time, highlight relevant products, and guide users based on preferences, budget, or use cases. Instead of generic suggestions, buyers get tailored prompts, comparisons and reminders that match their context. Instead of browsing multiple pages, shoppers get instant, context-aware suggestions and can complete actions like adding to cart or checking out within the same chat. This reduces friction, improves discovery and speeds up decision-making for all types of buyers.

StoreHippo has an AI commerce engine built directly into its core, so key AI features like semantic search, product recommendations, image enhancement through Magic Edit and AI-assisted catalogue creation come natively without any plugins. 

All AI features work out-of-the-box enabling brands to leverage them from day one. However, if your brand wants to build custom AI agents or advanced, business-specific AI workflows on top of the native capabilities, those are discussed separately and priced on a pro-rata basis depending on your use cases and scale.

StoreHippo’s built-in AI engine can automatically generate product listings for large inventories. For example, it can scan uploaded product images and data, then create clean, SEO-friendly titles, descriptions, categories and attribute mappings, without manual work. This makes the catalogue setup much faster when you have hundreds or thousands of products.

Yes, StoreHippo’s built-in AI image editor Magic Edit can automatically clean, enhance and resize product images. Magic Edit improves lighting, adjusts backgrounds and optimises size/format so product photos look consistent and professional without the need for manual editing.

StoreHippo’s AI feature for search uses semantic understanding instead of exact keywords, so it reads intent, context and synonyms to show the most relevant products instantly. This helps buyers navigate large or complex enterprise catalogues without confusion. The AI search engine also learns from each buyer behaviour and interactions and improves results over time, making product discovery faster, smoother and more accurate across enterprise B2B, B2C or multi-vendor marketplace setups.

Agentic AI assistants personalise buyer journeys by understanding each shopper’s intent, behaviour and past interactions. They adapt recommendations in real time, highlight relevant products, and guide users based on preferences, budget, or use cases. Instead of generic suggestions, buyers get tailored prompts, comparisons and reminders that match their context. Instead of browsing multiple pages, shoppers get instant, context-aware suggestions and can complete actions like adding to cart or checking out within the same chat. This reduces friction, improves discovery and speeds up decision-making for all types of buyers.