All Forschungszulage Statistics and Data (2026)
Forschungszulage statistics 2026: success rates, industry breakdown, company sizes and regional data. Data-driven insights for your R&D funding decision.
Software is no longer just "implementation" – it is often the core of genuine technological innovation, for example in new algorithms, complex system architectures, or AI-driven processes. Yet applications for the Forschungszulage in the software domain fail at an above-average rate, because projects are described too close to routine development or risks and novelty are not presented in a tangible way.
This post gives you a compact overview of what can be eligible, where the typical pitfalls lie, and how to document software innovation so that it becomes comprehensible in the Bescheinigung review.
The Forschungszulage is one of the best options for many software companies because it:
Important: this is not about "research for research's sake", but about innovation with technical risk – meaning projects where the outcome is not certain.
You can find more background on zeitmaker.com (initial assessment & first consultation).
Yes – software projects can be eligible if they go beyond standard development and venture into technological new territory. What matters is not whether you are building "SaaS" or "an app", but what is technically new and uncertain about it.
In practice, the challenge is that software is intangible. That is why the application must explain particularly clearly:
Typically not eligible are activities such as:
It becomes eligible when you, for example:
Practical tip from zeitmaker.com: Do not phrase it as "We are developing a new feature", but as: "We are solving a technological problem for which no established standard solution exists."
A common mistake: the product goal is new (for your company), but the solution approach is standard (for the market). It only becomes eligible when your project demonstrates:
The key question:
In software projects, risks are often formulated too broadly ("complexity", "AI hallucinates", "algorithms are new"). Better practice is:
Examples of good risk categories (depending on the project):
Agile methods are normal in development – but for the Forschungszulage you additionally need:
Important: typically eligible are the steps up to the prototype, not regular operations, rollout, maintenance, or routine improvements.
Many software companies work with agencies or freelancers. In principle, such engagements can be eligible for inclusion – but there are restrictions, for example regarding the place of establishment of the contractor (EU) and the nature of the cost allocation.
If a significant portion of your development is done externally, it is worth structuring the collaboration carefully (service descriptions, allocation to work packages, evidence of innovation-related activities).
We support you with the following:
If you want a quick initial assessment, also take a look at our reference projects.
No. What is eligible is not the business model, but the degree of innovation: a novel technical approach + technical uncertainty + a planned, systematic process.
Typically routine activities: migration, porting, configuration, standard integrations, debugging, documentation, maintenance, and support.
Generally not. You need a concrete work plan with work packages, goals, dependencies, and a clearly defined prototype endpoint.
Not in general terms ("hallucinations"), but project-specifically: Which target values (e.g. accuracy, robustness, latency) are critical – and why is it unclear whether you can achieve them with the planned approach?
Partially yes – depending on the framework conditions (including the contractor's place of residence/establishment and the nature of the engagement). Correct allocation to innovation-related work packages is essential.
Ask yourself: Where is the technical outcome open – and what exactly could fail? If you can answer that concretely, your chances are very good.
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Forschungszulage statistics 2026: success rates, industry breakdown, company sizes and regional data. Data-driven insights for your R&D funding decision.
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