Tactical Edge

Battlefield Layered AI Decision Engine

AI for the Warfighter

From the command post to the dismounted patrol — decision advantage at the point of contact. No cloud required.

275TOPS

GPU Compute

<100ms

Latency

7B+

Local LLM

IP67

MIL-STD

Choose Your BLADE

Three form factors, one unified software stack. Pick the configuration that matches your mission.

Portable

BLADE ALPHA

Alpha goes first - carry it in your ruck.

Form FactorBackpack / 5 kg
GPU100 TOPS
Storage2 TB encrypted NVMe
Sensors1-2 EO/IR + thermal
Power10-25 W field battery
AI Stack3B LLM + YOLO + Whisper
Connectivity100% offline
Vehicle / CP

BLADE BRAVO

Bravo is the backbone - bolts into your vehicle.

Form FactorVehicle mount / 10 kg
GPU275 TOPS
Storage4 TB mirrored NVMe
Sensors2-8 cameras GMSL/RTSP
Power15-60 W 12-24 V DC
AI Stack7B LLM + multi-CV + VLM
Connectivity100% offline
Command Post

BLADE CHARLIE

Charlie is your CP - runs on AWS Outposts.

Form FactorAWS Outposts rack
GPUEC2 GPU instances
StorageAmazon S3 + EBS
AI StackSageMaker + Bedrock
Network10 GbE + SATCOM
Fleet MgmtAll BLADE nodes
SyncAuto delta sync

All BLADE configurations share a unified software stack

How BLADE Works

Six layers from physical sensors to encrypted sync — every layer runs on-device.

SENSORS & INGEST

EO/IR CameraThermalAcousticCAN/ModbusGPSRFMQTT/NATS

PERCEPTION

YOLO DetectionObject TrackingOCRAnomaly DetectionWhisper ASR

AI RUNTIME

TensorRTTriton Serverllama.cppEmbeddingsFAISS/Qdrant

BLADE CORE

RAG EngineSOP AdvisorAlert TriageMission CopilotSensor FusionAudit

OPERATOR UI

ATAK PluginWeb DashboardVoice I/OTablet UIEvidence Export

DATA & SYNC

Vector DBEvent StoreEncrypted SSDDelta SyncmTLSPolicy Repl.

BLADE Core Modules

Purpose-built AI modules that run entirely at the edge.

Sensor Fusion

Correlates feeds from EO/IR, thermal, acoustic, and RF sensors into a unified operating picture. Reduces cognitive load by surfacing only what matters.

Local RAG Engine

Retrieves doctrine, SOPs, and field manuals from an encrypted local vector store. Answers operator questions with cited, authoritative references.

Alert Triage Agent

Prioritizes detections by threat level, proximity, and mission context. Filters noise so operators focus on actionable intelligence.

Operator Copilot

Natural language interface for querying system state, requesting sensor tasking, and generating situation reports. Voice and text input supported.

Sync & Federation

Delta-syncs data between BLADE nodes over constrained links. mTLS encryption, conflict resolution, and policy-based replication built in.

Audit & Explainability

Every AI decision is logged with full provenance - input data, model version, confidence score, and reasoning chain. Meets DoD explainability requirements.

Execution Roadmap

From zero to pilot-ready in 90 days.

Phase 1

Prototype

Days 1-30

  • Hardware selection and procurement
  • Base OS and AI runtime installation
  • Single-sensor integration (camera or thermal)
  • YOLO detection + basic alert pipeline
  • Operator dashboard MVP

Phase 2

Fieldable Alpha

Days 31-60

  • Multi-sensor fusion pipeline
  • Local LLM + RAG engine deployment
  • ATAK plugin integration
  • Voice I/O (Whisper + TTS)
  • Encrypted storage and audit logging

Phase 3

Pilot

Days 61-90

  • Field testing with operator feedback
  • Delta sync between BLADE nodes
  • Performance tuning and hardening
  • Operator training and documentation
  • Pilot deployment sign-off

30

Days to Prototype

60

Days to Alpha

90

Days to Pilot

100%

Offline

Zero

Cloud

Frequently Asked Questions

BLADE (Battlefield Layered AI Decision Engine) is a family of edge AI systems designed for military and defense operators. It runs entirely offline, processing sensor data through local AI models to deliver real-time decision support at the tactical edge - from dismounted patrols to vehicle platforms to command posts.

No. BLADE Alpha and BLADE Bravo operate 100% offline with zero cloud dependency. All AI inference, RAG retrieval, and sensor fusion run on local hardware. BLADE Charlie can leverage AWS Outposts for additional compute but is designed to operate in disconnected or denied environments.

BLADE Charlie runs on AWS Outposts - ruggedized rack infrastructure deployed at the command post. It leverages EC2 GPU instances, SageMaker for model management, Bedrock for foundation models, and S3/EBS for storage. This gives you cloud-grade AI capabilities with on-premises data sovereignty.

Yes. BLADE includes a native ATAK plugin that overlays AI-generated alerts, detections, and recommendations directly onto the ATAK map interface. Operators see fused intelligence without switching applications or workflows.

BLADE follows a 90-day deployment model: a working prototype in 30 days, a fieldable alpha with real sensor integration in 60 days, and a pilot-ready system with operator training in 90 days. All configurations share a unified software stack, so capabilities proven on one tier transfer directly to others.

See BLADE in Action

Schedule a classified demo or download the solution brief to share with your team.

sales@tacticaledgeai.com