01
Sense
Normalize camera, RF, acoustic, identity, wearable, radio, and partner inputs into source-linked mission events.
- Multi-source ingest
- Edge detection
- Source confidence
Architecture
Sensing, local AI, resilient transport, operations, fleet control, and review work as one system—not a dashboard over disconnected services.
6
Mission layers
9
Transport classes
5
Node platforms
1
Signed mission record
Execution model
01
Sense
Normalize camera, RF, acoustic, identity, wearable, radio, and partner inputs into source-linked mission events.
02
Understand
Route approved models by device, classification, capacity, and mission policy—then bind every output to its evidence.
03
Route
Move priority data across available links while local nodes retain useful mission state through disruption.
04
Act
Present the shared mission through command, operator, medic, analyst, observer, and systems surfaces.
05
Control
Govern the nodes, models, software, identity, classification, and posture carrying the mission.
06
Review
Reconstruct decisions, communications, evidence, and outcomes without rebuilding the story after the fact.
Link adaptation
Deployment
Phones, tablets, laptops, sensors, and edge compute operating locally or airgapped.
Local GPU or Kubernetes compute becomes the preferred resource without becoming a requirement.
Policy permits selected workloads and evidence to move upward when trusted bandwidth returns.
Synthetic mission data exercises the same product surfaces without live sensors.
Trust boundary
Classification and mission policy govern storage, movement, and inference.
Enrollment, posture, signed releases, rollback, and revocation stay auditable.
Operator actions and AI outputs retain source, model, policy, time, and custody context.
Technical evaluation
Bring the network, hardware, policy, and integration constraints.
Request technical review