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Applications

Application concepts, honestly labelled.

These are the systems we design and build. Every item carries a maturity label. We do not present concepts as deployments, and we do not publish customer results without permission.

Demonstration
Working system shown running on representative hardware and data.
Prototype
Functional implementation under active development and testing.
Concept
Engineered solution architecture we are ready to build with a partner.
Hands assembling a circuit board into a device housing
Concept
A-01

Manufacturing

Automated Manufacturing Defect Inspection

Problem
Surface defects on machined or moulded parts are caught inconsistently by manual inspection at high throughput.
Engineering approach
Synchronized area-scan capture and controlled lighting feed a detection-plus-anomaly model ensemble. The result drives a reject actuator and stores evidence for QA review.

Pipeline

  1. Trigger & capture
  2. Pre-processing
  3. Defect + anomaly models
  4. Reject decision
  5. Evidence log
Modern hospital operating room with surgical table and equipment
Concept
A-02

Healthcare & Medical Devices

Real-Time Surgical Video Analysis

Problem
Device teams need to add AI-assisted overlays to live surgical video without adding perceptible delay.
Engineering approach
A low-latency video path with GPU-resident segmentation and an overlay composited in the same frame budget. Built as an assistive visualization component for device integration.

Pipeline

  1. Video ingest
  2. Frame normalization
  3. Segmentation
  4. Overlay compositing
  5. Display output
Robotic arms working on a vehicle body in an automated assembly cell
Concept
A-03

Robotics

Intelligent Robotic Perception

Problem
Robots picking mixed, randomly oriented parts fail when perception is slow or poorly calibrated.
Engineering approach
Fused RGB-D perception with instance segmentation and 6-DoF pose estimation, producing grasp candidates within the robot's cycle-time budget.

Pipeline

  1. RGB-D capture
  2. Segmentation
  3. Pose estimation
  4. Grasp ranking
  5. Controller handoff
Operator adjusting a machine tool in a dimly lit workshop
Concept
A-04

Industrial Inspection

Industrial Anomaly Detection

Problem
Rare failure modes have too few labelled examples to train a conventional classifier.
Engineering approach
Models trained only on normal operation flag deviations in images or sensor signals and route them to operators for confirmation and continuous learning.

Pipeline

  1. Normal-only training
  2. Live scoring
  3. Thresholding
  4. Operator review
  5. Model update
Industrial process plant with a motor and stainless steel piping
Concept
A-05

Manufacturing

Multi-Sensor Monitoring

Problem
Cameras, vibration, thermal and process signals are monitored in silos, so correlated warning signs are missed.
Engineering approach
An edge node time-aligns heterogeneous sensor streams, runs fused models locally and publishes events to existing SCADA/MES systems.

Pipeline

  1. Multi-sensor ingest
  2. Time alignment
  3. Fused inference
  4. Event rules
  5. SCADA / MES publish
Fluorescence microscopy image of cell nuclei
Concept
A-06

Scientific Instrumentation

Scientific Imaging Analysis

Problem
Modern instruments produce data faster than offline analysis workflows can process it.
Engineering approach
Accelerated reconstruction and AI-based event detection run alongside acquisition, keeping only the data that matters and giving researchers results in minutes.

Pipeline

  1. Acquisition stream
  2. Reconstruction
  3. Feature detection
  4. Data reduction
  5. Researcher dashboard

Engineering consultation

Have an application in mind?

If your problem resembles one of these concepts, or none of them, we can assess feasibility on your own data.

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