Defense, Aerospace & Critical Infrastructure
Programs in this sector cannot send data to a hosted model, cannot accept unattributable AI output, and often cannot assume a network at all. Enfuse builds systems that work inside those constraints rather than around them.
- Air-gapped
- Designed for disconnected enclaves with signed offline updates
- Multi-INT
- Fusion across imagery, signals, sensor and document sources
- Full audit
- Every prompt, retrieval and output attributable to an identity
Why this sector cannot use hosted AI
The constraints below decide the architecture. Everything else follows from them.
No permitted egress
Inference, embedding, retrieval and logging all run inside the boundary. Model weights and updates arrive as signed offline artifacts through the program's transfer process.
Attributable output
Analytic products must be traceable. Every model interaction is logged against a program identity, with the retrieved sources recorded alongside the output.
Degraded and denied environments
Perception and decision loops close on edge hardware so the system keeps functioning when the link to the central site is intermittent or gone.
What Enfuse builds here
Delivered by embedded engineers working inside your environment, not handed over as a slide deck.
Air-gapped sovereign runtime
On-prem LLM orchestration with policy, audit and evaluation built into the runtime rather than each application.
- Signed offline model and configuration bundles
- Access-scoped retrieval over program document stores
- Full prompt, retrieval and response audit trail
- Evaluation harness run inside the enclave before model rotation
Perception at the edge
Camera, LiDAR, thermal and radar perception for perimeters, installations and platforms, fused and tracked on NVIDIA Jetson at the sensor.
- Time-synchronized multi-sensor capture and field calibration
- Detection, fusion and tracking within a millisecond latency budget
- Spatial grounding of tracks into site or mission coordinates
- Fleet update path for disconnected devices
Multi-source fusion and analysis
Correlate imagery, signals, sensor tracks and documents into a single operational picture with entity resolution across sources.
- Entity resolution and relationship mapping
- Change detection across imagery collections
- Transcription and triage of intercepted voice
- Report generation with classification handling
Hardware and software we deploy
Specified per site against sensor load, latency budget, thermal envelope and security boundary.
- NVIDIA Jetson AGX Orin / IGX Orin at the edge
- NVIDIA H200 / B200-class servers in the enclave
- Sovereign Runtime: orchestration, policy, audit, evaluation
- ROS 2 / Isaac ROS, DeepStream, TensorRT
- Existing program identity provider and SIEM
Bring us your constraints
Sensors, security boundary, latency budget, existing systems. We will tell you what is realistic and what it takes.