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Innovations
Engines
AOADN
OCO designs the AOADN data, AI, and sensor-integration engine for atmospheric-orbital anomaly detection, classification, and analysis across public data, private data, and approved hardware or multi-spectrum sensor sources.
AOADN requires careful separation between observation, classification, and conclusion. OCO’s public role is the data architecture: sensor source handling, event state, anomaly labels, model assistance, review evidence, and analysis interfaces. The system must evolve without overstating what any observation proves, so confidence, context, review state, and data quality remain visible throughout the workflow.
What OCO Builds
OCO builds AOADN as an atmospheric-orbital anomaly data system concept: sensor or source intake, observation records, event state, classification labels, review workflows, model assistance, evidence packaging, and analysis interfaces.
Operating Model
The operating model separates observation from interpretation. Events can be captured from public data, private data, or future hardware, then normalized with timestamp, location context, sensor quality, classification state, confidence, reviewer notes, and follow-up requirements.
Public Boundary
AOADN is described as proposed sky-intelligence infrastructure. Public language treats detections as observations or candidates, not conclusions. Proprietary sensor configuration, private datasets, classification rules, and security-sensitive deployment details remain private.