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.
