Four paths to a silicon-verified scorecard

A time-boxed paid engagement. You send the chip, the sensor modality, and the detection problem. Chrysalis runs it through the rig and returns a go/no-go feasibility report with preliminary accuracy and latency estimates on your actual silicon. Low procurement friction. Qualifies the downstream fixed-price engagement before any large commitment is made.

A fixed-price project engagement. Chrysalis takes your chip and detection problem through the full closed-loop rig: auto-labeled data collection via your sensor chain, training, deployment, and measurement. Deliverable is a model binary plus the complete 8-section silicon-verified scorecard - accuracy, latency, and energy measured on your hardware, aligned to MLPerf Tiny and EnergyRunner methodology. The scorecard is a compliance artifact, not a summary report.

A pre-trained base model - glass break, wake word, or a named acoustic class - adapted to your chip and sold as a per-deployment license. Faster time-to-result for customers whose use case matches a catalog class. Adaptation is verified on your silicon and delivered with a scorecard. Phase 2 SKU; available after the base model has been validated across multiple chips.

An annual subscription per deployed model covering drift monitoring, triggered retraining, and a full re-verification scorecard run on the same rig. Your compliance documentation remains tied to a living, reproducible scorecard history rather than a point-in-time artifact. Creates the audit trail that regulated verticals require under the EU AI Act.