Specialised behavioural prediction for complex commerce

Recommendation AI built to learn.

A continuously self-learning neural recommendation engine that turns customer behaviour into better product decisions and measurable revenue.

Built for prediction, not conversation.

Book a recommendation audit See how it learns

Trusted in real-world commerce

Largest tax free retailer in Northern Europe

The learning loop

It learns from every interaction.

Theklen uses behavioural feedback to keep improving what each customer sees. The recommendation changes, the customer reacts, and the system learns again.

1. Behaviour
Views, clicks and purchases

2. Neural learning
Patterns become predictions

3. Product ranking
The next-best products change

4. Feedback
Outcomes train the next decision

No static segments. No manually maintained recommendation rules. No prompt engineering.

Recommendations should optimise revenue, not similarity.

A mathematically similar product is not necessarily the product most likely to improve the commercial outcome.

Conversion rate
Help more visitors find a product worth buying.

Average order value
Predict relevant cross-sell and upsell opportunities.

Revenue per visitor
Optimise the value created by every shopping session.

Product discovery
Make large catalogues easier to explore.

A different kind of AI

Not all AI is built for recommendations.

Theklen neural engine

Learns from customer behaviour, continuously adapts product ranking and is designed specifically for behavioural prediction.

Manual rules

Useful for campaigns and constraints, but difficult to maintain as customers, products and contexts multiply.

Language models

Designed around language. Valuable for conversation, but not inherently built to optimise behavioural product ranking.

One engine. Four high-value use cases.

Personalised recommendations

Rank products around individual behavioural patterns rather than broad customer groups.

Cross-sell and upsell

Predict products most likely to extend the basket without relying on endless hand-built rules.

Personalised category ordering

Arrange large catalogues differently for different customers and contexts.

Next-best product

Predict what each shopper is most likely to engage with or purchase next.

The bigger the catalogue, the harder the problem. That is where Theklen gets interesting.

Rules may work for a small, stable range. As products, contexts and customer interactions grow, manual logic becomes a bottleneck. Theklen is built for recommendation problems where scale and behavioural complexity matter.

Small and stable
Rules can be enough.

Large and changing
Manual maintenance becomes painful.

Complex and high-volume
Continuous machine learning earns its keep.

Add intelligence without rebuilding your commerce stack.

Connect product data and behavioural events to Theklen, then return ranked recommendations to your webshop or app through the agreed integration layer.

Your webshop or app→Events and product feed→Theklen engine→Ranked recommendations

Customer proof

Recommendation technology proven with the largest tax free retailer in Northern Europe.

Theklen has been used in real-world commerce. The next step is to turn that experience into a quantified case study, using verified results rather than optimistic arithmetic.

See what Theklen could learn from your customers.

We will review your catalogue, traffic and current recommendation setup, then tell you whether there is a credible path to measurable improvement.

Book a recommendation audit

rando.parna@theklen.ai