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 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.


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.


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
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


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?
+A product recommendation engine analyses customer behaviour, product data, and contextual signals to deliver relevant suggestions across the shopping journey. For mature e-commerce businesses, the role of a product recommendations engine extends beyond upselling—it’s about creating frictionless discovery experiences that improve engagement, increase conversion rates, and drive repeat purchases at scale.
How do personalised product recommendations enhance the customer experience?
+Personalised product recommendations leverage behavioural and transactional data to adapt dynamically to each shopper. Rather than offering static lists, the system tailors suggestions based on intent, preferences, and real-time actions. This level of precision has become a key differentiator for brands looking to deliver superior e-commerce product recommendations and build long-term customer loyalty.
What are the advantages of using AI product recommendations over manual rule-based methods?
+AI product recommendations bring adaptability and scalability that traditional rule-based systems can’t match. As catalogues grow and user journeys become more complex, manual curation quickly hits its limits. AI models continuously learn from patterns and signals, making e-commerce product recommendation strategies more accurate, efficient, and responsive—even as business needs evolve.
How does your product recommendation software fit into existing e-commerce architectures?
+Our product recommendation software is built with an API-first, headless architecture, ensuring smooth integration with existing e-commerce platforms, search tools, and content systems. Whether you’re working with Shopify, Adobe Commerce, or a bespoke stack, the engine can be deployed as a modular intelligence layer, enriching existing experiences without disrupting core infrastructure.
What tangible business impact can personalised product recommendations deliver?
+When executed well, e-commerce product recommendations can deliver measurable results—from higher conversion rates and increased average order value to reduced bounce rates and improved product discovery. A well-implemented product recommendation engine acts as a strategic growth lever, aligning customer experience improvements with commercial objectives.
How does a product recommendation engine adapt to changing customer behaviour over time?
+A sophisticated product recommendation engine continuously learns from user interactions, purchasing patterns, and seasonal trends. By analysing these signals in real time, the system refines its product recommendations to reflect shifting customer preferences, ensuring the relevance and accuracy of suggestions as markets and behaviours evolve.
What role do e-commerce product recommendations play in retention and lifetime value?
+Effective e-commerce product recommendations aren’t just about immediate conversions—they’re instrumental in building long-term customer relationships. Personalised suggestions create a sense of relevance and familiarity, encouraging repeat visits, higher order frequency, and ultimately increasing customer lifetime value through more meaningful interactions.
Can AI product recommendations support multiple business objectives?
+Yes. Well-designed AI product recommendations can balance diverse goals such as conversion uplift, inventory clearance, cross-sell opportunities, and margin optimisation. Modern product recommendation software allows for configurable strategies and weighting, so brands can align recommendation logic with commercial priorities without compromising the customer experience.
How do personalised product recommendations perform across different channels?
+Personalised product recommendations maintain their effectiveness when deployed consistently across web, mobile, in-app, and chat interfaces. A unified product recommendations engine ensures customers experience coherent, context-aware suggestions no matter where they interact, reinforcing trust and reducing friction across omnichannel journeys.
What governance is needed to manage e-commerce product recommendation strategies at scale?
+As e-commerce product recommendation programs mature, governance becomes essential. This involves setting clear business rules, regularly reviewing algorithmic outputs, and aligning recommendation strategies with brand and merchandising objectives. Modern product recommendation software provides dashboards, reporting, and fine-tuning capabilities to give teams full control without compromising automation benefits.


















