AI Solutions

Recommendation Engines

Relevance ranking that lifts basket size and time on site, measured against a holdout.

Outcome: Recommendations with a proven revenue lift over the current logic.

What we usually find

Related items are picked by category rules written years ago. Nobody has tested whether they beat showing nothing at all.

What the work covers

Scope is agreed in writing before anything starts. If a line here is not relevant to you, it comes out of the plan and out of the price.

  • Behavioural event collection and feature engineering
  • Collaborative and content-based models with a sensible cold start
  • Live serving with latency budgets that fit the page
  • Holdout group so lift is proven rather than assumed
  • Business rules for stock, margin and exclusions

Typical tooling

Indicative, not fixed. The stack follows your constraints and your team, not our habits.

  • Python
  • PyTorch
  • Vector search
  • Redis
  • BigQuery

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