Amazon Rekognition Review: Is It The Right Image Recognition Software For Your Team?

Amazon Rekognition excels at image and video analysis, particularly for facial recognition, object detection, and scene identification. Before shortlisting, verify that your use case fits its core strength: analyzing static images or video streams where AWS infrastructure is acceptable.

The service has two key limitations to test in a demo: facial recognition accuracy drops significantly in low-light conditions and with partial face angles, and the API charges per image analyzed, which can escalate quickly with high-volume workloads (test your expected monthly volume against the pricing calculator). Integration is straightforward if you're already on AWS—the service connects directly to S3, Lambda, and other AWS tools.

If your stack is non-AWS, you'll need to build custom connectors or use the REST API, which adds development overhead. Pricing traps to watch: charges apply for every API call (including failed requests), storage costs for indexed faces accumulate, and video analysis is billed per minute of content processed, not per frame.

Verify in your demo that Rekognition's confidence thresholds for object and face detection align with your accuracy requirements—the default settings may flag false positives in edge cases. If you need real-time processing of live camera feeds, test latency against your SLA.

For compliance-sensitive use cases (healthcare, finance), confirm that AWS's data retention and deletion policies meet your regulatory requirements before committing.