Explainable edge-AI: fusion and classification you can audit.
CORE is the edge-AI: explainable classification and multi-sensor fusion, run at the edge, with auditable outputs — source-agnostic, so VAERN and third-party sensors go into the same picture.
Fusion and classification, explained.
CORE fuses whatever sensor feeds are available — VAERN's own, the customer's, or third-party — and classifies tracks, and shows why. Explainability is the point: the operator sees the reasoning behind each call.
- Explainable classification.
- Multi-sensor fusion.
- Runs at the edge.
- Auditable outputs.
- Source-agnostic ingest.
In the decision loop.
Multi-sensor detection: radar, passive RF and EO/IR — VAERN's own or existing third-party sensors.
Resilient mesh links forward nodes into one network.
Explainable edge-AI fuses sensors and classifies tracks.
The operator sees one air picture and authorises the response.
Effectors integrate later via an authorised partner — effector-agnostic by design.
Details.
| Function | Explainable classification & fusion |
| Compute | Edge |
| Explainability | Auditable outputs |
| Inputs | VAERN and third-party sensors — open interfaces, fitted to each integration |
| Specifications | Specified per deployment |
Figures are set per deployment — every site gets the mix it needs, and we publish no numbers we cannot stand behind.
AI classifies; it does not decide. Explainability keeps the human in the loop meaningful.