Article

Diagnose Data Pipeline Sync Errors with AI

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May 7, 2025

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4 min read

Summarize this article with:

Reliable data movement is the backbone of modern businesses. At Airbyte, we are constantly researching and testing ways in which AI can be used to simplify the creation and maintenance of data pipelines. When data sync jobs fail, it can disrupt workflows, affect downstream analytics, and delay decision-making. In such moments, time is of the essence—you need to find the root cause fast and fix it even faster. Data is critical to business decisions.

Today, we’re thrilled to introduce a new AI co-pilot to help you diagnose sync failures identified in event logs — no more scrolling through detailed logs or manually Googling error messages. Let AI do the work for you!

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With AI, diagnosing sync issues is as simple as tapping a button. From any failed sync job, just open the job log and click “Explain this error”. In seconds, the AI analyzes the relevant portion of the log, identifies the likely root cause, and offers a clear explanation—often with direct suggestions on how to resolve the issue.

Whether it’s a missing API key, a schema mismatch, or a timeout from a third-party system, AI helps surface the exact problem so you can act quickly and confidently. It transforms raw, unstructured logs into actionable insights.

This new feature is especially helpful for data teams managing a large number of connectors or complex sync schedules. Instead of relying on engineers to sift through logs line by line, your AI co-pilot can accelerate triage and reduces downtime. It’s like having an AI assistant on call 24/7.

AI Log Co-Pilot is now available in Airbyte Cloud Teams. To learn more, keep reading about Airbyte Cloud.

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