Case Study: Findify achieves faster feature development and near-zero Spark DevOps with Databricks

Findify - Customer Case Study

Findify builds machine-learning Smart Search for e-commerce stores to boost conversions and revenue. Their data pipeline relied on self-managed Apache Spark, Jenkins jobs, and custom scripts—maintenance was time-consuming, error-prone, and caused delays (about an extra developer month per year), reducing team productivity and slowing feature delivery.

Moving to Databricks’ hosted Spark and integrated notebook workspace removed DevOps overhead, enabled easy scaling, and improved global collaboration and prototyping. As a result Findify achieved near-zero maintenance, faster feature development (smart autocomplete and adaptive search), streamlined ML pipelines into Elasticsearch and PostgreSQL, and measurable time savings that improved customer experience and revenue.

Findify

Meni Morim

Co-founder and CEO