Reactor AI Factory

The Complete ML Platform
at the Tactical Edge.

Edge-Native AI Factory for Disconnected Operations

A complete machine learning platform that deploys to a single device at the network edge. Train, serve, and monitor models where your data lives—no cloud required.

Enterprise ML platforms assume datacenter infrastructure and persistent connectivity. Your mission operates at the tactical edge. Reactor delivers the full ML lifecycle - data ingestion through model serving - on hardware you can carry into contested, disconnected, and austere environments.

CURRENT CHALLENGE

Enterprise ML Can't Deploy Forward

Current ML platforms assume datacenter infrastructure and persistent connectivity:

  • Cloud Dependency:
    Training and inference require continuous network access

  • Infrastructure Requirements:
    Kubernetes clusters, GPU farms, and storage arrays

  • Security Constraints:
    Sensitive data cannot leave tactical environments

  • Operational Complexity:
    MLOps requires specialized teams at central sites

OUR SOLUTION

AI Factory That Fits in a Pelican Case

Reactor packages the complete ML lifecycle into a single deployable unit:

Single-Device Deployment:
Complete platform on one edge compute device

Fully Disconnected:
Train and serve models without any connectivity

GitOps-Managed:
Declarative config with offline update bundles

Zero-Trust Security:
mTLS, encrypted secrets, air-gapped by design

Full Stack
ML Lifecycle
Coverage
1
Device
Deployment
0
Cloud
Dependencies
100%
Offline
Capable

Why Reactor?

  • Single-Device Deployment

    Complete ML platform on one edge compute device. No racks, no datacenter, no external dependencies.

  • Fully Disconnected Operation

    Train and serve models without any network connectivity. Air-gapped by design, not as an afterthought.

  • GPU-Accelerated

    Native support for NVIDIA DGX systems. Distributed training with PyTorch, TensorFlow, and XGBoost.

  • GitOps-Managed

    Declarative configuration with Flux. Reproducible deployments, version-controlled infrastructure.

  • Zero-Trust Security

    mTLS everywhere, identity-aware access, encrypted secrets. Secure by default.

  • Optional Connectivity

    When networks are available, secure tunnel access for remote management without exposing ports.

Target Environments

Reactor operates where traditional ML platforms can't.

Forward Operating Bases
Shipboard / Afloat
Mobile Command Posts
Air-Gapped Facilities
Expeditionary Sites

GitOps-Native Operations

Reactor's entire configuration lives in Git. Flux continuously reconciles cluster state with your repository. Change a value, push a commit, and the platform updates itself—whether you're connected or carrying updates on a secure transport device.

Declarative Configuration
Version-Controlled Infrastructure
Reproducible Deployments
Automated Drift Detection
Offline Update Bundles
Reactor AI Factory Logo

Bring ML to the Mission

Ready to deploy enterprise ML capabilities at the tactical edge?

Contact Us