PANIAX SEQUENCE INTELLIGENCE

Behaviour-driven product recommendations for modern retailers.

Move beyond generic “customers also bought” widgets. Sequence Intelligence learns from real customer journeys. How baskets evolve, which items naturally bundle, and how intent shifts step-by-step, generating real-time recommendations that adapt instantly as shoppers browse and buy.

Explore how it works below, then try the live recommender demo in the Demo tab.

Behaviour-driven recommendations, not guessing

Paniax Sequence Intelligence is a recommendation engine that learns from real purchase sequences, not static rules or lookalike products. It understands how customers actually shop: which items appear together in baskets, how those baskets change over time, and how intent shifts as people browse and refine what they want.

The engine adapts in real time as products are added or removed, so every suggestion supports the customer’s path to purchase, increasing conversion, uncovering long-tail products, and reducing manual merchandising effort.

Why it matters
  • Higher conversion and average order value.
  • Better discovery of long-tail products.
  • Less reliance on manual rules and campaigns.
  • Evidence-based, behaviour-level insights.
What makes it different
  • Sequence-aware modelling of full baskets.
  • Complement & substitute recognition.
  • Adaptive learning on your own data.
  • Designed for commercial impact, not toy demos.
Who is it for?

Retailers and commerce teams who want measurable uplift in conversion, basket size, and product discovery, without building an in-house data science stack.

Typical retail scenarios
  • Fashion & apparel: outfit completion & seasonal bundles.
  • Home & lifestyle: multi-item sets & accessory pairing.
  • Beauty & personal care: routine-based sequences and regimens.
  • Food & grocery: refill cycles and recipe-driven baskets.
Talk to us

Curious how this would work on your catalogue and data? Start with a low-friction evaluation based on a small sample of historical sales.

Book an evaluation call

How it works

  1. Provide sales data sample.
    We analyse a small slice of your historical sales to understand patterns and validate data quality.
  2. Model on your behaviour.
    A tailored model is trained only on your data, learning how your customers combine products and how intent shifts across sessions.
  3. Connect via simple API.
    Your front-end or commerce platform calls a lightweight real-time API to fetch recommendations for each basket or session.
  4. Retrain as behaviour evolves.
    Periodic retraining keeps recommendations aligned with new products, seasonality and emerging trends.

What it unlocks

  • Higher conversion rates through relevant, context-aware suggestions.
  • Higher average order value via intelligent cross-sell and bundle suggestions.
  • Reduced irrelevant suggestions that damage trust and clutter the interface.
  • Lower return rates by steering customers to the right complements and substitutes the first time.
  • Faster product discovery so customers reach suitable products with less friction.

Plans & rollout

Evaluation

Free to start. We use a small sample of your sales data to prove performance and demonstrate how the model learns from your customers’ behaviour.

Production

Transparent flat monthly subscription starting at €500 / month, tailored to data volume, traffic, and integration complexity. No usage penalties, no extra fees; support and model re-training included.

Implementation is designed for minimal engineering effort. no in-house ML team required, and no heavy infrastructure to maintain.

Beyond “similar items” carousels

Traditional recommenders focus on colours, categories or keyword similarity. They miss the underlying reason why customers combine items, and they struggle to tell a complement from a substitute.

Sequence Intelligence is basket- and journey-aware. It models the full sequence of actions. Which products appear together, how the cart changes, and how intent evolves, and optimises recommendations around that.

The result is a recommendation layer that feels helpful and intelligent instead of generic, and that is tuned to your actual customer behaviour, not a generic template.

Why choose Paniax Sequence Intelligence
  • Model is trained solely on your data.
  • Captures full-basket sequences, not just single clicks.
  • Recognises both complements and substitutes.
  • Flat, predictable pricing with retraining included.
  • Low integration effort; no internal ML team required.

Want to see it with your own products and data?
Email sales@paniax.com to start an evaluation.

Your basket
1 item(s)

This page is a product recommender demo built on a catalogue of about 3,600 SKUs.

What this demo illustrates

This example showcases several capabilities found in modern, production-grade commerce intelligence engines:

✅ Sequence-based learning. Understands the customer journey across browsing and purchasing steps.

✅ Co-purchase pattern detection. Identifies which products naturally belong together in real baskets.

✅ Context-aware recommendations. Suggestions adapt to the user's real-time behavior and session context.

✅ Next Best Product logic. Prioritizes the product most likely to increase relevance, engagement, or cart value.

✅ Pre-basket & post-basket intelligence. Works both during product browsing and after items are added to the cart.

✅ Affinity-based ranking. Uses SKU-level relationships instead of static category rules or manual merchandising.

✅ Dynamic reweighting. Real-time recalculation as the basket evolves, improving prediction relevance on every interaction.

✅ Non-generic, data-driven behavior. Learns directly from behavioral data, not preprogrammed if-X-then-Y logic.

A real customer deployment would train on your own behavioral data and be retrained periodically as products, seasons and buying patterns change.

Results are for demonstration purposes only.
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