01
Perception
We make machines see and sense: industrial cameras, depth, ultrasound, instruments and multi-sensor arrays, calibrated and synchronized.
Engineering intelligent systems for the physical world
Intelligence engineered for the real world.
We build intelligent automation systems that connect perception, AI, and physical operations, transforming complex industrial processes into real-time decisions.
01 · Perceive
Cameras, depth, imaging & sensors
02 · Understand
Accelerated AI inference
03 · Decide
Deterministic, low-latency logic
04 · Act
Robots, PLCs & operators
Engineering disciplines
under one roof
- Computer Vision
- Sensor Fusion
- Real-Time Inference
- GPU Computing
- Edge Deployment
- Imaging Pipelines
- Robot Guidance
- C++ / Python
- Industrial Integration
Core capabilities
From photons to decisions. Engineered as one system.
Intelligent automation fails at the seams between sensors, models and machines. We engineer across all three, so the system works on the line and not only in a notebook.
02
Machine intelligence
We develop and optimize models for detection, segmentation, anomaly and state recognition, tuned to the accuracy the process demands.
03
Physical action
We close the loop: reject gates, robot motion, PLC signals and operator guidance, inside the time budget of the process.
Industries
Built for operations where precision is non-negotiable.
- I-01ManufacturingHigher yield, less scrap and consistent quality from perception systems that keep pace with production.
- I-02Healthcare & Medical DevicesEngineering partnership for device teams building real-time imaging and video-based products.
- I-03RoboticsPerception, fusion and guidance software that lets robots handle variability.
- I-04Scientific InstrumentationAccelerated acquisition and analysis pipelines that keep up with modern sensors.
- I-05Industrial InspectionRepeatable, documented inspection of assets, components and infrastructure.
- I-06Research & DevelopmentEngineering capacity to turn promising prototypes into robust, deployable systems.
Solutions
Seven engineering practices. One standard of delivery.
Each practice is a production engineering discipline with defined deliverables, validation criteria and handover.
S-01 · Featured
Intelligent Visual Inspection
We engineer inspection systems that look at every part, on every shift, and make consistent pass/fail decisions in the time budget of your line. From optics and lighting to models and reject logic, we design the full loop.
View solutionOur engineering approach
Production is the only benchmark that matters.
Demos are easy. Systems that run every shift, survive changeovers and earn operators' trust are not. Four principles guide every engagement.
How we engineer
- 01
Physics first
Optics, lighting, sensor placement and timing decide most outcomes before a model is trained. We start there.
- 02
Latency is a requirement
We set an end-to-end time budget at the start and engineer every stage to fit inside it.
- 03
Measured, not claimed
Success criteria are agreed up front and verified on your hardware, with your data, in realistic conditions.
- 04
Built to be owned
Documented architecture, reproducible builds and source ownership options. No black boxes.
Edge AI & real-time processing
Intelligence where the data is born.
Sending every frame to the cloud costs time, bandwidth and control. We deploy accelerated AI next to the sensor, on-device or on an on-site edge server, so decisions arrive while they still matter.
- Zero-copy streaming pipelines with bounded, predictable latency
- Models optimized for embedded and industrial accelerators
- Distributed processing across multiple edge nodes
- Data stays on-site for privacy, IP protection and uptime
Edge node · field deploymentStreaming
Research & innovation
We invest in the problems our customers will face next.
Our internal R&D programme explores techniques that shorten development time and widen what can be automated. Explore our application concepts to see where it is heading.
View applications
R&D-01
Few-shot anomaly detection
Learning what “normal” looks like when defect examples are rare.
R&D-02
Multi-sensor fusion
Combining vision, depth, motion and process signals into one reliable state.
R&D-03
Accelerated reconstruction
Moving imaging algorithms from offline research code to live operation.
R&D-04
Synthetic data & simulation
Training and testing perception before hardware is on the floor.
Project delivery
A disciplined path from feasibility to production.
Every engagement is staged with clear exit criteria, so you invest progressively as risk comes down.
- 01
Discovery
We study the process, the physics and the constraints, and define measurable success criteria and a latency budget.
- 02
Feasibility
We test on your real parts, signals or images to establish what accuracy and speed are achievable before major investment.
- 03
Engineering
We build the system in iterative increments: sensing, models, pipeline, integration and interfaces.
- 04
Validation
We verify against the agreed criteria on target hardware, under realistic conditions, with documented results.
- 05
Deployment
We commission on site, train your team and hand over documentation, source options and operating procedures.
- 06
Evolution
We monitor performance, retrain on new data and extend the system as your operation changes.
Engineering consultation
Have a process that needs to see, decide and act?
Tell us about the parts, signals or images you work with. An engineer, not a salesperson, will reply with an initial assessment of feasibility and next steps.