Security And Trust
Control the devices, models, data, and decisions that make up the mission.
EdgeLance is built for environments where AI outputs, device posture, model provenance, and evidence custody matter as much as the interface.
Trust Layers
Security is enforced across the product spine.
Device trust
Enroll approved nodes, verify posture, track hardware/software state, and degrade or quarantine devices that no longer meet policy.
Model trust
Approve model artifacts, track provenance, bind model/RAG loadouts to missions, and preserve receipts for what ran where.
Data trust
Route inference by data sensitivity, keep source evidence attached to AI outputs, and preserve audit context for review.
Mesh trust
Use authenticated control-plane data, link scoring, trust-aware routing, TTL/loop prevention, and priority replay for DDIL movement.
Operator trust
Keep human challenge, override, approval, and rationale in the mission timeline instead of hiding decisions inside a black box.
Deployment trust
Support signed bundles, courier delivery, rollback points, and offline proof harnesses before field validation.
Governance
Built for customer-controlled AI.
Local-first by policy
Prefer on-device or base GPU inference before approved cloud compute, depending on mission policy and link state.
Evidence-coupled AI
Every AI answer should point back to source clips, sensor signals, confidence, mission rules, and operator actions.
Signed audit posture
Security-sensitive actions should produce receipts: model approval, device enrollment, courier transfer, readiness override, export, and wipe.
Airgapped delivery
Software Courier is designed for missions where network delivery is unavailable or undesirable.
Evaluation Notes
Designed honestly for pilots, accreditation, and field proof.
Pilot Gates
What to prove before field expansion.
Identity and enrollment
Can the customer enroll approved devices, assign mission roles, verify posture, and revoke access without breaking the mission workflow?
Artifact custody
Can model, RAG, and software packages be signed, staged, delivered, verified, and tied to deployment receipts?
AI accountability
Can every recommendation be traced to source evidence, model context, policy, operator action, and final outcome?
DDIL behavior
Can the platform preserve useful operation through link loss, then replay priority events without flooding the network?
Export control
Can review material be packaged for commanders, legal, partners, or allies with the right scope and audit trail?
Bring your security team into the demo.
The right evaluation includes model governance, device posture, courier flow, audit receipts, and deployment authority.
Request Security Review