01 / DETECT
Identify relevant objects
Detect multiple object classes across complex scenes, variable image quality and challenging operating conditions.
AI computer vision for defence and ISR
Turn video streams into operational awareness.
A modular AI computer vision layer for real-time object detection and tracking across UAV, EO/IR, ISR and operator-support systems. Adapted and evaluated on customer-provided video.
REPRESENTATIVE SYSTEM OUTPUT
Built for defence OEMs and system integrators
Designed as a modular software capability for integration into existing and future video-based systems.
A modular capability layer
Designed to extend existing video-based systems.
The technology supports operators and analysts by detecting, classifying and consistently tracking relevant objects without replacing the customer's existing workflow.
02 / TRACK
Maintain temporal context
Associate detections across frames to provide more stable information and reduce short-lived, inconsistent indications.
03 / ADAPT
Fit the customer's environment
Adapt models and validation criteria to specific sensors, object classes, environments and operational priorities.
Target applications
One core capability. Multiple operational contexts.
The technology is sensor- and platform-oriented rather than limited to a single vehicle or mission profile.
Analysis of live or recorded airborne video streams.
Support across visible-light and thermal imagery.
Persistent monitoring and operator assistance.
Additional software capability within existing workflows.
Adaptation to customer-defined sensors, object classes, environments and operational requirements.
Built for difficult imagery
Operational video is not laboratory data.
Small objects, motion, clutter, partial occlusion and inconsistent image quality require a complete data, model and validation workflow rather than a generic detector.
01
Small and distant objects
Development includes targets represented by only a limited number of pixels.
02
Variable sensor conditions
Models can be adapted to the customer's representative footage and environment.
03
Measured performance
Evaluation uses agreed criteria and a held-out acceptance set to separate adaptation from final validation.
Customer-data evaluation
A clear path from video to a licensing decision.
A limited, paid evaluation answers the practical question: how does the capability perform on the customer's own material?
01
Scope and NDA
Define the use case, target classes, constraints and evaluation criteria.
02
Paid evaluation agreement
Agree deliverables, responsibilities, schedule and commercial terms before work begins.
03
Secure data transfer
Receive representative customer video and establish a held-out acceptance subset.
04
Adapt and validate
Prepare data, fine-tune the model and measure performance against agreed criteria.
05
Results and licensing
Present the report, demonstrate results and define a suitable deployment and licence model.
Evaluation to deployment
The customer retains control of system integration.
The technology is structured as a separately licensed software capability. Evaluation, deployment boundaries and integration interfaces are agreed without requiring access to the customer's source code.
The initial evaluation delivers measurable results and a technical report without transferring source code or unrestricted model weights.
Deployment can be structured around a documented runtime or API aligned with the customer's hardware and security requirements.
Licensing can be tailored to an agreed programme, platform, deployment scope or OEM relationship.
Start with your own material
Evaluate the technology on your own data.
Start with a limited, paid customer-data evaluation using representative video from your target sensor and operating environment.