Your edge model fits. Now make it accurate.
Recover lost accuracy without rebuilding your model stack.
Deployment blocked
Deployment unblocked
Built for the deployment gap.
The big model worked
The small model ships
But production is blocked
Perforated can help
Deployment Recovery Pipeline
Compressed Model
Fits on edge. Meets latency target. Misses production accuracy threshold.
Recovery Pass 1
First recovery iteration removes ~30% of remaining error. Boundary detection improves.
Recovery Pass 2
Second pass removes +20% additional remaining error. Segmentation quality continues to improve.
Projected Outcome
~50% total remaining error removed. Deployment-ready recovery path within edge constraints.
Example directional recovery path for compressed edge segmentation workloads.
Designed to fit into your existing pipeline.
Typically tested through your existing validation set.
Same inputs
Your model sees the same images, frames, depth inputs, or tensors it already sees today.
Same deployment path
Keep your existing runtime target, export path, and edge deployment workflow.
Accuracy recovery layer
Add Perforated AI during training or fine-tuning to recover lost accuracy after pruning or compression.