Agent 04 · inspect-and-release
Reject the defects. Keep the good units.
Automated visual inspection routinely scraps good product to be safe. The inspect-and-release agent senses sub-visible particulate, cosmetic defects, cracks, and CCI at line speed, catching real defects without the false-reject tax.
The problem
False rejects are a hidden tax on yield.
Rule-based AVI systems are tuned to over-reject: a borderline shadow becomes a scrapped unit. On high-value biologics, that caution costs more than the defects it prevents, and still misses novel defect modes.
- Fixed thresholds can't tell glare from a crack.
- Every false reject scraps a released-value unit.
- Novel defects slip past hand-coded rules.
How it works
Perceive, classify, decide, with a reason.
- 01
Multi-view capture
High-resolution imaging across angles and lighting states resolves glare from genuine defects.
- 02
Learned classification
Models trained on real defect libraries separate particulate, cracks, and cosmetics from artifacts.
- 03
Grounded decision
Each accept/reject cites the signal and rule behind it: auditable, not a black box.
- 04
Feed the flywheel
Confirmed calls retrain the model, tightening precision on your specific products.
Capabilities
The full defect surface.
Sub-visible particulate
Detects fibers, glass, and protein aggregates below the visible threshold.
Cosmetic defects
Scratches, stains, and fill-line anomalies caught without over-rejecting.
Cracks & chips
Structural container defects that threaten sterility flagged reliably.
CCI prediction
Predicts container-closure integrity risk at line speed, before leak testing.
Lyo cake inspection
Assesses cake structure, collapse, and meltback for freeze-dried product.
Explainable calls
Every reject carries a localized reason for reviewer trust.
Economics
Recover the yield you were scrapping.
A one-point drop in false-reject rate on a high-value biologic can return more than the entire deployment. The agent lifts precision without lowering the safety of your true-defect catch rate.
Model the yield in the twin →Under the hood
Precision without escapes.
True-defect recall held high
Precision gains never come at the cost of letting critical defects escape.
Explainable rejects
Reviewers see the localized evidence behind each call.
Retrains on your product
Confirmed outcomes tighten the model for your exact molecules and containers.
Rule-based vs. Sterira
Learned beats thresholded.
| Behavior | Rule-based AVI | Inspect-and-release agent |
|---|---|---|
| Distinguishes glare from defect | Poorly | Reliably |
| False-reject rate | High | −61% |
| Catches novel defects | No | Yes |
| Explains each call | No | Yes |
"The false-reject line item on our high-value product dropped by more than half. That recovered yield paid for the deployment in a quarter."
Sterile injectables site
FAQ
Common questions.
It augments and can drive existing AVI hardware, or run on new vision stations. The intelligence layer is what changes, not necessarily the cameras.
Precision improvements are constrained so true-defect recall is never reduced below your validated threshold. Escapes are the line we protect first.
Against your defect library with documented performance, then run advisory alongside current inspection before any release-impacting deployment. See validation.
Stop scrapping good units.
Pilot the inspect-and-release agent and measure the false-reject drop.