Models need to adapt
New environments, sensors and objects can expose gaps in model performance. Teams need a repeatable way to evaluate and improve deployed models using field observations.
Solution
Scaleout Tactical AI Network.
Deploy, operate and improve AI across devices and sites.
A software and engineering solution built on Scaleout Edge, bringing together tactical computer vision, onboard drone AI and local model improvement within your infrastructure.
The problem
Keep useful AI connected to changing conditions.
Local data needs a workflow
Operational sites generate more footage than teams can review. Selecting useful observations and supporting annotation locally helps turn that data into training material.
Connections cannot be assumed
Limited bandwidth and disconnected devices interrupt central workflows. Local processing and learning need to continue, with shared updates coordinated when links are available.
Initial applications
Start with the workflow your team needs.
The initial focus combines tactical computer vision and AI for drones. Select the applications, devices and sites relevant to your evaluation, then expand the scope as results and requirements develop.
Tactical computer vision
Establish detection, data selection, annotation and model improvement for counter-UAS, ISR or range surveillance using local observations.
Explore tactical computer visionAI for drones
Deploy models to onboard compute, retain observations during disconnection and synchronise with ground infrastructure. Validate the workflow against your chosen hardware in structured field evaluation.
Explore AI for dronesWhat comes together
Shared infrastructure.
A coordinated delivery.
Scaleout Edge
The software platform manages model versions, deployment, reported metrics and federated learning within your chosen infrastructure.
Ground nodes and devices
Vision Ground Nodes support local inference, review and training. Edge AI Companions run models on onboard compute and retain observations for later synchronisation.
Engineering and integration
Scaleout engineers help establish models, data workflows and integrations, then support evaluation and knowledge transfer around the agreed application.
Connection changes
Local work continues. Shared improvements can wait.
Local inference and learning
Devices run models and collect observations. Ground nodes support local review, annotation and training while the site’s local connections remain available.
Coordination across sites
The control plane coordinates cross-site learning and the distribution of approved models when sites are connected.
When a link drops
The affected site continues local work. Cross-site model exchange resumes when connectivity returns.
From evaluation to deployment
Establish value before expanding.
Agree the scope, success criteria and responsibilities at each stage. Progress depends on evaluation results, integration readiness and your deployment requirements.
Build a repeatable capability.
Knowledge transfer helps your team or chosen partner take ownership of data workflows and model improvement as the deployment develops.
Lab evaluation
Connect selected data, models and equipment. Establish the workflow and baseline performance, and agree what should be tested in the field.
Field validation
Evaluate with representative sensors and operating conditions. Check inference, local learning and behaviour through connection changes against the agreed requirements.
Pilot
Onboard users, refine annotation and update workflows, and assess integrations. Validate learning across participating sites where this is part of the scope.
Broader deployment
Expand to additional devices and sites as results support it. Agree ongoing support, operating responsibilities and the security requirements for deployment.
Get started
Define your first evaluation.
Tell us about your application, sensor feeds, equipment and sites. Work with Scaleout engineers to define a useful starting point and the evidence needed to decide what comes next.
Scaleout
Provides software and engineering support for the agreed workflow, including model adaptation, integration, evaluation and training for the customer team.
Your team
Provides domain expertise, data access, equipment and operating requirements. Retains control of model approvals, operational decisions and the direction of further development.
Your chosen partners
Can supply hardware, systems integration, annotation personnel or on-site support. Responsibilities are agreed around your procurement and operating arrangements.
Security requirements and accreditation support are scoped around your environment. Your operational data, trained models and decisions remain under your control.
Discuss an evaluation