Hello @Matias Haller ,
Thank you for sharing the details.
Based on the observed behavior and recent service patterns, the increased processing time is most likely related to backend queue delays driven by regional load and request distribution, rather than any regression, configuration issue, or SDK-related concern.
This is a known and occasionally observed behavior under high-demand conditions, and applying the above optimizations can help improve consistency and overall processing times.
At present, there are no active service-wide outages specific to Document Intelligence in the East US region. However, latency issues can occur under certain backend conditions, even when requests are successfully accepted and processed.
This behavior is typically associated with internal processing dynamics rather than request failures, and the following factors are known to influence processing time:
- Regional load and demand patterns as East US is a high-traffic region
- Queue waiting time before execution begins
- Batch processing behavior and request aggregation
- Document size, complexity, and page count
- Temporary fluctuations in service throughput or backend health
Since Document Intelligence operates on an asynchronous processing model, the total processing duration includes both:
- Queue time - waiting for processing slot
- Execution time - actual document analysis
Under higher load conditions, queue delays can significantly increase, which leads to longer overall completion times without generating any explicit errors.
Please let us know if the response was helpful and if the latency issue has been resolved
Thank you