Defense AI Software for Autonomous Systems and Counter-UAS

AI That Works When Connectivity Fails

DIU-selected · Blue UAS-aligned · ATO-ready

We Build the Software that Gets AI from Lab to Field

Validated, Repeatable, and Ready for DDIL

Generate synthetic training data. Validate AI before deployment.
Deploy to edge platforms in DDIL environments.
No cloud dependency. No vendor lock-in. Auditable at every step.

What Defense Programs Face

Detection is too slow.

Cloud systems fail when comms go down. Swarms overwhelm operators. Fixed c-UAS cannot move with the force.

Training data does not exist.

Field collection is dangerous and expensive. Threats evolve faster than acquisition allows. Biased data causes missed detections.

Edge systems must work alone

DDIL is the norm. GPS gets denied. Legacy systems were not built for contested environments.

Compliance delays fielding.

ATO timelines add months. Vendor lock-in limits options. Threats do not wait.

What Success Looks Like

Detection that holds in contested conditions

Sensor-to-shooter in seconds, not minutes

Auditable evidence for ATO and program reviews

Deploy to any edge platform without re-engineering

Adapt to new threats without new data collection

How SensorOps' Purpose-Built software Addresses these challenges

TargetModeler

Generate labeled EO/IR datasets in minutes. Cover edge cases. Keep models current.

SynDOJO

Validate AI before fielding. Measure Pd, false alarms, operator response. Produce audit-ready evidence.

TacOS

Run AI on SWaP-constrained hardware. Fully offline. Multi-sensor fusion. API-driven.

use cases

Counter-UAS detection and tracking​

Autonomous ISR payloads​

Maritime domain awareness​

Perimeter and base security​

Route clearance and convoy protection​

Mobile and expeditionary operations​

Use Cases

Counter-UAS detection and tracking

Autonomous ISR payloads

Maritime domain awareness

Perimeter and base security

Route clearance and convoy protection

Mobile and expeditionary operations

Capabilities

Offline Operation

Offline Operation

Full capability without cloud connectivity

GPS-denied capable

GPS-denied capable

Works when GPS fails​

SWaP-optimized

SWaP-optimized​

Runs on constrained hardware

Offline Operation

Multi-sensor fusion

Fewer false alarms

Classified environments

Classified environments

Unclassified through Secret

Open architecture

Open architecture

YOLO, ONNX, TensorRT, TAK/ATAK

Developer-friendly

Developer-friendly

REST APIs, containers, CI/CD

Why SensorOps?

DE-RISK DEPLOYMENT

Validate performance before fielding.

ADAPT FASTER

New training data in minutes, not months.

NO CLOUD DEPENDENCY

Fully offline operation in DDIL environments.

NO VENDOR LOCK-IN

Bring your own models and export outputs.

REDUCE OPERATOR BURDEN

Fewer false alarms and clearer displays.

Ready to deploy AI that works in contested environments?

See SensorOps in action
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