ISR Sensing
Multi-modal payload integration: EO/IR, mmWave radar, acoustic. Payload-agnostic ingestion layer handles heterogeneous sensor streams without vendor lock.
View capabilityKESTRELSENSE
ISR-grade sensing. Edge AI inference. Zero cloud dependency.
Kestrelsense builds sensor fusion and on-device inference systems for unmanned platforms operating in denied, degraded, or disconnected environments.
Kestrelsense was founded to close the gap between sensor data and autonomous decision — specifically for platforms that cannot afford a cloud roundtrip. We build for the weight, latency, and power budgets that commercial AI stacks ignore. Every decision in our architecture reflects one constraint: inference must complete on-device, at mission speed, regardless of connectivity. We are not a general-purpose AI company. We do not build autopilot stacks. We build the sensing and inference layer that feeds the autopilot — and we build it for environments where the cloud is not an option.
CORE CAPABILITIES
Three disciplines. One platform.
Edge AI Inference
On-device neural inference optimized for <50ms latency at <15W SWaP envelope. Supports NVIDIA Jetson, Hailo-8, and custom FPGA targets.
View capabilityAutonomous Integration
Mission-layer APIs for UAS, UGV, and USV integration. Human-on-the-loop interface hooks. Compatible with ROS 2, MAVROS, and custom GCS stacks.
View capabilityARCHITECTURE
From sensor to decision, on-device.
01
Multi-Modal Ingest
Sensor data from EO/IR, radar, and acoustic payloads is timestamped and ingested through a unified hardware abstraction layer.
02
Edge Inference Engine
Compressed neural models run on-board compute — detecting, classifying, and tracking objects at mission-relevant latency without uplink.
03
Mission Interface
Structured outputs feed operator displays or autonomous decision loops via standard GCS / ROS 2 APIs. Human override always in the loop.
PERFORMANCE ENVELOPE
Built for contested environments.
Every design decision in the Kestrelsense stack is made under three constraints that matter in the field: Size, Weight and Power. We reject approaches that require connectivity, GPU-class compute, or centralized inference.
Inference latency
< 50 ms
Power envelope
< 15 W (edge compute)
Connectivity required
None (fully air-gapped)
Sensor modalities
EO/IR, mmWave, Acoustic
Platform targets
UAS, UGV, USV
Inference hardware
Jetson Orin, Hailo-8, FPGA
ENGAGE
Technical briefings available for qualified programs.
Kestrelsense works directly with DoD program offices, Tier-1 autonomy primes, and defense R&D labs evaluating edge-AI ISR payloads for unmanned platforms. All engagements begin with a structured technical briefing — NDA execution precedes any detailed technical disclosure. Reach us at [email protected] or submit a request below.
Request Technical Briefing