Image upscaling / super-resolution

Resolution is raised on small, compressed or legacy images while keeping edges and text legible rather than smoothing them away. It is typically run before a reading or recognition model, so the downstream pipeline sees the best available version of the frame. Both the original and the upscaled version are kept, so nothing is lost by running it.

You can use the models we operate or bring your own model and we run it on your cluster. Work arrives as an API call, a batch over a folder or bucket, or a resident on-premise service, and results return as structured output with a per-job audit record.