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Digitalisation funding for IT and software development

Digital and IT teams have to deliver fast and, at the same time, build systems that last. What used to be enough, namely shipping features quickly, now has to comply with regulation, scale economically under AI and data loads, and stand up to clear cost and impact criteria. A large share of that work can qualify for funding, but in practice it is rarely recognised as such because it does not always look like classic research.

Heineken
UltiMaker
Coolblue
ABN AMRO
KPN
Vattenfall
PostNL
ProRail
NS
Jumbo
ANWB
Bynder
Universiteit Utrecht
Nedap
VDL
Gasunie
Fugro
Unit4
Zeeman
Basic-Fit

The developments shaping your roadmap

AI has become infrastructure, not a feature. What matters is the foundation it requires: data pipelines, model integration, monitoring, governance and operational reliability.

The cost of digitalisation is a boardroom topic. Cloud, compute, licences and energy consumption affect scalability, margin and investment decisions, so teams must demonstrate efficiency as well as functionality.

Energy efficiency & decarbonisation

From equipment replacement to process heat: programmes for lower energy use and CO₂ are currently especially well funded.

Automation & robotics

Investment in robotics, sensor technology and connected equipment that secures productivity without replacing people.

Digitalisation & Industry 4.0

From the digital twin to connected manufacturing: funding for modernising production IT.

The programmes behind it

Which instruments apply depends on the market. In most European markets, digital and IT work falls under development funding rather than a dedicated digitalisation scheme. Depending on the project, that means tax-based instruments, national grant programmes or thematic calls.

Depending on the project, European instruments such as the EIC Accelerator and EUREKA Eurostars apply as well.

What to watch out for in this sector

In digital and IT projects, the funding potential often lies not in the subject itself but in the technical uncertainty behind it. That is exactly where most stumbling blocks arise in practice.

01

Routine instead of development

Many projects are described as software development but read in the application like implementation, configuration or integration of known solutions. A project only becomes eligible once it is clear which technical uncertainty had to be resolved and why standard tools or known patterns were not sufficient.

02

Too little delimitation of the development share

Digital projects often contain mixed activities: architecture, prototyping, testing, UX, data modelling, operations, maintenance and rollout sit close together. If it is not cleanly separated which work is genuine development and which work belongs to business as usual, the eligible share is often reduced.

03

Unclear evidence for development time

In software projects, hours are usually the largest cost item. Without traceable time recording, sprint documentation, tickets, work packages or technical decision records, it is difficult to demonstrate later who worked on which R&D element and when.

How we work

We do not start with the application but with your roadmap: which parts of your digital and IT projects contain real technical uncertainty, and which belong to normal delivery? Our specialists know both the schemes and the assessment practice in software, data and AI projects.

Numbers you can hold us to

95%

Success rate

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Resources & Insights

I only need to supply the necessary documents and Ignite Group takes care of the rest. It gives us the freedom to focus on developing our technology and selling our products.

Eric Pellis Co-owner and Managing Director, INUTEQ

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FAQs about funding advisory

View all FAQs

Yes, if the project carries technical uncertainty. What does not qualify is the pure application of known methods, for example a standard integration or configuration. Software development can qualify where new solution paths have to be tested and the outcome is still technically open.

Purely using existing AI models does not usually qualify. What can count, however, is the development work around them, for example where models are adapted, integrated, monitored or developed further so that they can run reliably, traceably and economically.

Yes, but eligible development components have to be cleanly delimited from the start. Even in agile projects you need traceable work packages, technical objectives and time accounting. If who worked on what is only reconstructed from sprints afterwards, the documentation quickly shows gaps.