Research, development & emerging technology services

Applied research and specialist engineering

We provide research and development services across AI, quantum computing, post-quantum cryptography, key management, IoT and OT/ICS security, autonomous systems, robotics, and satellite communications. Each engagement connects a business or technical need to a research plan, implementation scope, and evaluation criteria.

Our services also cover edge computing, digital twins, virtual and augmented reality, spatial applications, and large-scale data analysis. We assess the architecture, tools, data, integration requirements, and security controls needed to move from an initial concept to a working prototype.

From feasibility to implementation

We develop proofs of concept and prototypes, document the test environment, and evaluate performance against agreed criteria. The deliverables explain the results, technical dependencies, and next steps so your team can plan development, integration, or a wider rollout.

We support national and international research programmes and project partnerships with technical research, prototype development, evaluation, and documentation. Responsibilities, milestones, intellectual property, and handover are agreed at the start of the engagement.

Turn an emerging technology into a testable question

Research should begin with a decision your organisation needs to make: whether a proposed sensor works in a particular setting, whether an AI approach handles the available data, or whether a new architecture meets an operational constraint. We define the hypothesis, comparison baseline and evidence needed for that decision. This keeps a feasibility study focused even when the technology itself is changing quickly.

Prototype connected systems and digital twins

A connected-system prototype may need physical devices, telemetry, application interfaces and a model of the process being observed. We agree which parts are real, simulated or outside the experiment. For a digital twin, the relationship between measured state and model assumptions must be visible. Results should explain what the prototype demonstrates and what further work is needed before operational use.

Plan technical research with ownership and reproducibility

A research engagement can define work packages, datasets, experimental conditions, reporting milestones and intellectual-property arrangements. Test materials and results should be organised so an authorised reviewer can understand how a conclusion was reached. Dependencies on specialist equipment, external laboratories or third-party software are identified early, rather than left to emerge after a prototype has been promised.

Decide whether to stop, extend or industrialise

A feasibility result can be valuable even when it shows that an idea does not meet the agreed requirements. We compare the observed outcome with the original criteria and explain remaining uncertainty. Recommendations can include a narrower use case, another experiment or an implementation plan addressing reliability, security, operating cost and support ownership.

Common questions