Capabilities

Local AI, mesh, fleet, and mission software in one operating layer.

EdgeLance is built for teams that need modern AI and sensor fusion without giving up control of devices, models, data, or mission continuity.

EdgeLance mesh network capability visualization

Product Architecture

Six layers from sensor input to mission record.

Sense

Turn existing field inputs into structured mission events.

RTSP/IP camerasMotion-triggered clipsAcoustic eventsNFC/IFFRF and radio metadataDrone and sensor feeds

Understand

Use local AI to summarize what changed, why it matters, and what evidence supports it.

Object detectionAudio transcriptionScene summariesRAG mission librariesEvidence-linked answersModel loadouts

Route

Move the right data to the right node when links, power, compute, and trust keep changing.

EdgeLance MeshStore-forwardQoS priorityTrust scoringCompute routingDDIL operation

Act

Give each role a mission-specific workspace with actions, decisions, and collaboration.

Shared mapRole overlaysAI directiveMedic flowsTaskingMission chat

Control

Manage devices, models, software, and security posture as part of the mission workflow.

MDM postureDevice enrollmentSigned courierModel registryRollbackAudit ledger

Review

Preserve the mission record for command, legal, training, partners, and next-mission learning.

Capture historyDecision timelineSource chainAAR supportExportsKnowledge base updates

Technical Depth

More than a dashboard around AI APIs.

The product value is in orchestration: choosing where AI runs, how evidence is preserved, how mesh data moves, and how users challenge or trust outputs.

01

Local model orchestration

Routes language models, transcription, segmentation, and object detection across local, base GPU, and approved cloud resources by policy, classification, and compute capacity. Supports open models like Gemma, Llama, and Whisper alongside customer-approved alternatives.

02

Mission RAG libraries

Lets users stage reference material before a mission: SOPs, ROE, base procedures, local patterns, equipment guides, med protocols, and partner briefings.

03

Event-driven camera AI

Avoids burning GPU on continuous analysis. Motion, audio, scene change, or operator request triggers deeper inference and evidence capture.

04

Mesh simulation and planning

Models node count, link health, device mix, camera load, power pressure, and compute bottlenecks before the mission starts.

05

Apple and consumer device hardening

Uses consumer hardware as mission nodes with managed software, local models, courier packages, posture checks, receipts, and role-specific controls.

06

Evidence-coupled decisions

AI recommendations stay connected to source clips, sensor readings, confidence, mission rules, and operator challenges.

Packaging

One suite, or focused modules.

EdgeLance can be sold as the full mission suite or licensed around the parts a customer needs first.

EdgeLance Mission

The operator, medic, command, analyst, and review workspace.

EdgeLance Mesh

A stand-alone mission-aware mesh and data movement layer.

EdgeLance Fleet

Device, software, MDM, courier, and model readiness management.

EdgeLance Connectors

Integrations for cameras, radios, TAK-style tools, cloud LLMs, base GPU servers, and partner systems.

Walk through the product, not a slide deck.

The best evaluation is a guided mission flow: plan, live map, medic view, camera evidence, AI directive, mesh health, fleet readiness, and review.

Request Demo