AI Matchmaking Pipeline

Built scalable data pipelines to support AI-assisted matchmaking and future personalization.

Key Takeaways:

Data processing limited pairing accuracy

User data could not be efficiently processed and scored, limiting the ability to generate high-quality matches.

We enabled scalable data preparation for matching

A structured data pipeline was introduced to support pairing logic and future AI-driven enhancements.

Databricks-based data transformation

User data was ingested into Databricks and transformed into dbt models, enabling scalable scoring and candidate generation aligned with business rules.

Foundation established for AI-driven matchmaking

The platform enabled more accurate pairing logic and unlocked future personalization initiatives.

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Governed Metrics for AI

Single logic across every interface

Compliance Reporting

Reporting automated

Audience Segmentation

Targeting efficiency improved