AI PRODUCT RECOMMENDER

Instant Relevance, Effortless Discovery

Intelligent recommendations and context-aware answers drive engagement and boost conversions.

Shoppers expect intuitive search as well as guidance.1 Those who engage with AI chat complete purchases 4x more often; guidance from conversational AI drives 47% faster purchases; and for returning customers, AI chat drives 25% higher AOVs.

As of 2025, personalised product recommendations is the top AI use case for 50% of retailers. But businesses are stuck with systems that can’t interpret intent or provide personalisation.2

Close the expectation gap for shoppers. Drive revenue for your store.

Our Solution:
Product Recommender + IKA

Our Solution: Product Recommender + IKA

Our Product Recommender and Intelligent Knowledge Assistant (IKA) work together as a hybrid AI solution that understands human queries and provides contextually relevant answers and personalised product recommendations.

The Product Recommender analyses user intent and behaviour together with catalogue data to suggest the most relevant products—not just “similar items.”

The IKA acts as a domain-aware assistant that understands and answers natural-language questions such as “Will this fit?” or “What’s the best alternative to Product X?” so customers aren’t sent off on a dead-end FAQ hunt.

Our hybrid AI solution transforms static catalogues into dynamic platforms for personalised discovery.

Replace choice overload with product discovery that converts.

Key Capabilities

The power of a hybrid AI solution means your business can finally deliver a five-star shopping experience at scale. Our combined Product Recommender and IKA solution offers true domain-specific intelligence to fundamentally transform how customers interact with your catalogue—and expertly guide them from query to successful purchase.

By integrating our system’s capabilities, you can expect immediate improvements in engagement, a measurable reduction in shopper frustration, and a significant revenue boost.

Natural Language Understanding

Our AI interprets multi-criteria, conversational queries—even vaguely worded ones—and returns accurate results so “no results” frustration is eliminated.

Natural Language Understanding
Intelligent Product Recommendations

Intelligent Product Recommendations

Hard-coded rules limit discovery. Deliver hyper-relevant suggestions by combining user intent and behaviour with product attributes.

Contextual Product Q&A

Provide instant, contextual answers—powered by your catalogue data—for sizing, compatibility, policies, and FAQs. Reduce support load and shorten time-to-purchase.

Contextual Product Q&A
Easy Omnichannel Deployment

Easy Omnichannel Deployment

Our headless, API-first solution integrates effortlessly across all customer touchpoints: Web, mobile, chat, and in-store.

Deploy a unified, headless AI platform that transforms customer interest into revenue.

Seamless Integration with Your Tech Stack

Our Product Recommender + IKA solution is built to integrate seamlessly with your existing architecture, delivering immediate intelligence without the need for costly replatforming.

Search and Indexing Engines

Search and Indexing Engines

Works with platforms like Typesense, Algolia, and Elasticsearch for high-performance search and filtering

PIM / ERP / CRM

Pulls live data for product attributes, inventory, and customer context

PIM / ERP / CRM
CMS / Commerce Platforms

CMS / Commerce Platforms

Headless, API-first design ensures compatibility with modern platforms including Shopify, Adobe Commerce, and Storyblok

Bring intelligence to product discovery.

Supercharge your storefront with AI-driven recommendations and contextual answers.

Abandoned searches and lost clicks leaving revenue on the table?
We can help.

FAQ

What is a product recommendation engine, and why is it important for modern e-commerce?

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How do personalised product recommendations enhance the customer experience?

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What are the advantages of using AI product recommendations over manual rule-based methods?

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How does your product recommendation software fit into existing e-commerce architectures?

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What tangible business impact can personalised product recommendations deliver?

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How does a product recommendation engine adapt to changing customer behaviour over time?

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What role do e-commerce product recommendations play in retention and lifetime value?

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Can AI product recommendations support multiple business objectives?

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How do personalised product recommendations perform across different channels?

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What governance is needed to manage e-commerce product recommendation strategies at scale?

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