Case Study: Symend boosts performance and cuts costs with Airbyte

Symend cuts data refresh latency by 75% with Airbyte

Symend, a leader in intelligent collections, faced significant challenges scaling its data infrastructure using Microsoft Azure Data Factory. The legacy system suffered from poor performance, high costs, and cascading pipeline failures that hindered its AI and analytics goals. This necessitated a change to a more robust data integration solution.

By implementing Airbyte, Symend gained a distributed architecture that processes data in parallel, eliminating cascading failures and reducing data refresh latency from two hours to as little as thirty minutes. This migration resulted in approximately $900,000 in annual cost savings and enabled new AI innovations, including a self-service chatbot for natural language data analysis. Airbyte provided the reliable, high-performance data movement foundation Symend required.

Symend