The Engineering
Behind Every Decision.

A complete technology stack — spanning signal acquisition, high-speed vision, GPU-accelerated processing, and 3D spatial intelligence — engineered to meet the demands of critical industrial environments.

How It Works

Signal acquisition hardware

High-Speed & Precision
Signal Acquisition

Our signal acquisition system delivers exceptionally stable, high-fidelity capture across all input channels simultaneously. Designed for environments where signal integrity is critical, it handles a wide range of physical inputs — from vibration and acoustics to voltage and current — preserving every transient and high-frequency event from the point of sensing through to processing.

Synchronised Multi-Channel Capture
All input channels are captured in precise synchronisation — eliminating timing discrepancies across the full sensor array regardless of channel count.
Real-Time Spectral Analysis
Frequency, time-domain, and modal decomposition run concurrently onboard — results are ready as each acquisition frame completes.
High-Fidelity Signal Conditioning
Precision analog input stages maintain signal integrity across the full dynamic range — from low-level sensor outputs to high-amplitude industrial signals.
High speed camera system

High-Speed Image
Capture & Vision

Our high-speed imaging system captures every pixel across the full frame at the identical instant, ensuring geometrically accurate results even during rapid motion and high-speed events. A dedicated synchronisation interface connects multiple cameras with tight timing precision, keeping stereo and multi-angle setups spatially coherent throughout the entire capture sequence.

Simultaneous Full-Frame Capture
Every pixel is exposed at the same instant across the entire sensor — eliminating motion skew and geometric distortion even at extreme capture speeds.
Multi-Camera Synchronisation
All connected cameras are triggered in precise unison over a dedicated synchronisation line — independent of the data network and consistent across every capture.
Direct Sensor-to-Processor Transfer
Captured frame data is transferred immediately to the processing layer with no intermediate buffering — keeping the pipeline continuous and latency low.
GPU compute hardware

Zero-Copy
GPU Pipeline

Our processing pipeline keeps all data resident within the compute layer from the moment it leaves the sensor. Preprocessing, calibration, normalisation, and inference are executed as a continuous sequence of parallel operations — forming an unbroken, low-latency path from raw sensor input to final result with no unnecessary data movement in between.

Zero-Copy Data Architecture
Sensor data is transferred directly into the processing layer without intermediate copies — keeping the pipeline lean and the data path fully deterministic.
Concurrent Processing Streams
Pre-processing and inference execute in parallel across independent compute streams — data transfer and computation overlap continuously throughout the pipeline.
Optimised Model Compilation
AI models are compiled and optimised for the target hardware at deployment time — maximising inference throughput with no compromise to accuracy on industrial tasks.
3D sensor fusion and point cloud

Multi-Modal
3D Sensor Fusion

Our fusion engine combines depth, structured light, stereo imaging, and inertial sensing into a single, continuously updated spatial model. The geometric relationship between all sensors is tracked and corrected in real time — accounting for environmental changes such as thermal drift and mechanical vibration to sustain spatial accuracy across the full working volume throughout every measurement.

Continuous Spatial Calibration
Inter-sensor geometry is solved and updated continuously during operation — maintaining spatial consistency without manual recalibration between runs.
Motion-Aware Data Processing
Inertial measurements are integrated between depth capture cycles to compensate for target motion — producing clean spatial data even during dynamic events.
Dense Spatial Mapping
Fused sensor output is encoded into a structured volumetric representation — enabling fast spatial queries and surface analysis by downstream AI modules.

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