Self-serve, no-code AI personalization solution for Shopify merchants providing product recommendations, upsells, and cross-sells.
DTC e-commerce brands lack customer data and resources to build Amazon-like recommendation engines, limiting personalization and sales from upsells/cross-sells.
DTC e-commerce brands lack customer data and resources to build Amazon-like recommendation engines, limiting personalization and sales from upsells/cross-sells.
No-code AI platform using multi-modal technology for product recommendations that works with minimal data, quick Shopify integration, and revenue uplift.
No-code AI platform using multi-modal technology for product recommendations that works with minimal data, quick Shopify integration, and revenue uplift.
YC lists as inactive; founder interview indicates shutdown
YC lists as inactive; founder interview indicates shutdown
Suggestr offers a no-code personalization platform designed for e-commerce brands on Shopify. It leverages multi-modal AI to deliver Amazon-style product recommendations, enabling merchants to boost sales through upsells and cross-sells without requiring data science expertise.
The platform supports features like 'You May Also Like,' 'Frequently Bought Together,' 'Trending This Month,' 'Recently Viewed,' dynamic bundles, handpicked recommendations, and post-checkout one-click upsells. These can be placed on product detail pages, cart pages, 404 pages, and more. Integration takes under 30 minutes, making it accessible for brands of all sizes from small to enterprise.
Suggestr uses innovative multi-modal AI that analyzes product images, text, and customer behavior. This approach requires 100x less data than traditional methods, creating a network effect across clients for stronger recommendations. The system emphasizes performance, loading in 13ms, faster than a typical Google search.
Suggestr offers a no-code personalization platform designed for e-commerce brands on Shopify. It leverages multi-modal AI to deliver Amazon-style product recommendations, enabling merchants to boost sales through upsells and cross-sells without requiring data science expertise.
The platform supports features like 'You May Also Like,' 'Frequently Bought Together,' 'Trending This Month,' 'Recently Viewed,' dynamic bundles, handpicked recommendations, and post-checkout one-click upsells. These can be placed on product detail pages, cart pages, 404 pages, and more. Integration takes under 30 minutes, making it accessible for brands of all sizes from small to enterprise.
Suggestr uses innovative multi-modal AI that analyzes product images, text, and customer behavior. This approach requires 100x less data than traditional methods, creating a network effect across clients for stronger recommendations. The system emphasizes performance, loading in 13ms, faster than a typical Google search.
SaaS subscription with free trial
SaaS subscription with free trial
Shopify merchants, DTC e-commerce brands (SME to enterprise)
Shopify merchants, DTC e-commerce brands (SME to enterprise)
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Hiring: unknown
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Hiring: unknown
Focused on direct-to-consumer brands selling on platforms like Shopify. It addresses the gap for DTC merchants lacking the data or teams to build in-house recommendation engines like those used by marketplaces such as Amazon.
Focused on direct-to-consumer brands selling on platforms like Shopify. It addresses the gap for DTC merchants lacking the data or teams to build in-house recommendation engines like those used by marketplaces such as Amazon.
Merchants can implement AI-driven personalization to increase online store revenues. The solution aims to help e-commerce stores achieve higher conversion rates and average order values through automated, intelligent product suggestions.
Merchants can implement AI-driven personalization to increase online store revenues. The solution aims to help e-commerce stores achieve higher conversion rates and average order values through automated, intelligent product suggestions.
Co-founded by Aditya Mehta, a technologist with experience building recommender systems and e-commerce operations, and Oleksii Sidorov, an AI researcher with publications in machine learning and prior exits. The YC Winter 2022 batch company was based in Singapore.
Co-founded by Aditya Mehta, a technologist with experience building recommender systems and e-commerce operations, and Oleksii Sidorov, an AI researcher with publications in machine learning and prior exits. The YC Winter 2022 batch company was based in Singapore.
