Workshop makeover

Connecting data across the workshop

 
A single source of truth that drives smarter decisions

 

 

Expert insight

Leader spotlight

 

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Thomas Aardal

A CTO at Nagarro. He is an architect and consultant for cross-functional technology practices, focusing on cross-cutting technologies such as enterprise integration, open-source platforms, and process automation.

 

 

Building an AI-powered personalization engine at a global scale

When we held our Fluidic Advisory session, we assessed the workshop, and one theme stood out: personalization was happening, but without structure. Millions of wish lists arrived in different formats: vague, inconsistent, frequently changing, and matching each child with the right gift had become increasingly difficult. Intuition and manual review were no longer enough. The workshop needed a system that could interpret context, understand preferences, and make ethical decisions at scale.

The transformation

The ToyMatch system was designed as an AI-powered personalization engine built on three pillars: unified data, contextual intelligence, and ethical transparency. A centralized data foundation brings together wish lists, behavior signals, and real-time inputs. Layered onto this is the Yuletide Toy Graph, a dynamic model capturing relationships between children, toys, age groups, trends, and constraints.

With this foundation, ToyMatch interprets wishes, predicts interests, and recommends toys with clarity and fairness. And because the system learns from every season, accuracy improves continuously.

Behind the build

 

Fluidic-Enterprise

1. Unified data foundation

A centralized Toy Data Lake aggregates wish lists, app submissions, and behavior signals while maintaining privacy.

2. Context-rich intelligence

The Yuletide Toy Graph maps evolving relationships between preferences, toys, regions, and age groups.

3. AI-driven matching

LLMs interpret free-form wish lists into structured needs; predictive models and reinforcement learning refine matches each season.

4. Ethical & transparent controls

Bias mitigation, explainable scoring, override options, and a fairness seal ensure inclusivity and transparency.


5. Operational integration

ToyMatch connects directly to production, inventory, and routing systems so recommendations automatically inform manufacturing and delivery.

6. Continuous improvement

Post-season feedback, ratings, and experience data train models for better accuracy and operational efficiency.

The workshop today

ToyMatch now delivers personalization at global scale that is both accurate and ethical. Children receive gifts that truly reflect their interests, operations run with greater clarity, and the system becomes smarter with every holiday cycle.


Personalization works when intelligence, context, and fairness move together. That’s what we built into ToyMatch.

 

Thomas Aardal
CTO, Nagarro