TacOS
Edge AI Runtime for Autonomous Operations and Sensor Fusion
Execute AI analytics, sensor fusion, and
mission logic on small, power-limited hardware.
Offline-capable. Operator-controlled.
Why TacOS?
Most edge AI assumes constant connectivity and developer access. TacOS executes on constrained devices, operates without cloud or GPS, and lets operators adjust workflows without code.
Built for Low SWap Constraints
Runs on sub-10W edge platforms.
True offline operation
Detect, decide, and act in DDIL environments.
Operator-configurable
Drag-and-drop pipelines. No developers required.
Sensor-to-decision on device
Raw feeds to real-time actions at the edge.
Multi-sensor fusion
Correlate radar, EO/IR, AIS, ADS-B, RF, acoustic, and space feeds.
Reason-coded outputs
Provenance, confidence scores, and audit trails on every action.
Capabilities
Detect, track, decide
Millisecond-level response. No backhaul required.
Fuse multiple sensors
Time-aligned, geo-referenced tracks with confidence scoring.
Adapt in the field
Swap models and thresholds without rebuilds.
Coordinate across platforms
Multi-vehicle and swarm support across air, ground, and maritime.
Integrate existing tools
Multi-vehicle and swarm support across air, ground, and maritime.
Run standard models
YOLO, MMDet, ONNX, TensorRT. No lock-in.
Generate evidence
Audit-ready bundles for replay and after-action review.
The Stack
Pipeline Builder
Drag-and-drop sensors, models, rules, outputs. No code.
Model Runtime
ARM/x86, Android/Linux, GPU acceleration.
Sensor Adapters
Radar, EO/IR, AIS, ADS-B, RF, acoustic ingest.
Fusion Engine
Multi-sensor correlation, time alignment, geospatial normalization.
Mission Logic
Rules, geofences, triggers, checklists at the edge.
Edge I/O
Camera ingest, radio links, storage, TAK/GIS integration.
Health & Logs
Diagnostics, audit logging, exportable summaries.
Why Teams Trust It?
Field-proven
Built for rough comms, variable power, harsh conditions.
Secure by design
RBAC, mTLS, signed artifacts, audit logging, SBOM. PKI-compatible.
Classified environments
Unclassified through Secret.
Store-and-forward
Maintains operations under constrained links.
Fits the SensorOps loop
Pairs with TargetModeler and SynDOJO for full lifecycle.
Operational impact
Edge-speed decisions
Detection-to-action in milliseconds, no backhaul.
Bandwidth efficiency
Transmit tracks and alerts instead of raw video.
DDIL resilience
Continue operations when GPS denied or communications degrade.
Hardware efficiency
High availability on SWaP-constrained platforms.
Audit-ready
Every action logged with reason codes.
Use Cases
Defense
c-sUAS, UAS ISR, perimeter security, route clearance, EW-degraded operations.
Public Safety & Infrastructure
Mobile command, event security, pipeline patrol, port security.
Industrial & Logistics
Yard automation, warehouse counting,
inspection QA.
OEMs & system integrators
Drop-in edge runtime that supports customer deployments without designing a new inference stack.
Workflow
Each rep feeds the next. Performance climbs while costs stay flat.
Pricing & deployment
Sub-10W edge platforms to server-class. Linux and Android. ARM and x86. On-prem with optional cloud-assist.
Program Impact at a Glance
Power envelope
Sub-10 W edge targets supported in typical TacOS configurations
Latency
Model-to-action response under 50 ms in representative setups
Deployment timeline
Initial deployment on supported devices commonly completed within a day
Common questions
Yes. Fully on-device processing, decisions, and actions.
Linux, Android. ARM, x86. GPU acceleration supported.
Yes. Drag-and-drop, no code.
YOLO, MMDet, ONNX, TensorRT. No lock-in.
Native bidirectional CoT messaging.
RBAC, mTLS, audit logging, SBOM. Secret-certified.
Upload models via secure transfer. No rebuild needed.