πŸ’‘ The key facts about the Forschungszulage at a glance.

Forschungszulage for MedTech & HealthTech Companies

Date: February 23, 2026β€’Author: Erich Lehmann

TL;DR – Summary

If you are genuinely building innovation in MedTech or HealthTech (e.g. AI, software, medical devices, diagnostics, data platforms), you can use the tax-based Forschungszulage to refinance a large portion of your costs β€” predictably, annually, and without classic "pitch" logic. Since 28 March 2024, SMEs receive 35%, and from 1 January 2026 the assessment base increases to €12M (up to €4.2M Forschungszulage p.a. for SMEs). Real example: voize secured €314,825 for AI-assisted care documentation.

Terms & context: Updates 2024 & 2026 Β· Calculation Β· Case Study voize

I see it time and again in MedTech and HealthTech projects: the truly expensive phases do not start at roll-out, but before β€” in prototypes, iterations, and testing, validation, interface work, and dealing with technical uncertainties. This is exactly where the tax-based Forschungszulage comes in: it rewards systematic development and makes innovation projects financially more predictable.

In this article I will show you which MedTech/HealthTech projects are typically eligible, what pitfalls frequently arise in practice β€” and how you can use the Forschungszulage as a cash flow lever. As a concrete example I refer to our case study on voize's AI-assisted care documentation (secured funding: €314,825): Case Study voize at dieforschungszulage.de


1) What is the Forschungszulage β€” and why is it so relevant for MedTech/HealthTech?

The Forschungszulage is a tax-based incentive for innovation projects (in the statutory context: R&D). Unlike classic grant programmes, it is often the most predictable and sustainably usable lever β€” especially for teams that develop continuously (software, algorithms, medical devices, diagnostics, data platforms, etc.).

In MedTech & HealthTech in particular, what tends to come together is exactly what the logic of the Forschungszulage favours:

  • Technical uncertainty (does the method work reliably in practice / in real data / in clinical workflows?)
  • High integration complexity (HIS/PMS, devices, interfaces, standards, data quality)
  • Validation and quality assurance (stability, robustness, performance, error rates, safety)
  • Iterative product development rather than "build once, done"

If you can structure and document this properly, the Forschungszulage can meaningfully reduce the financial burden of innovation β€” without forcing your project into a short-term funding window.


2) How large is the funding? (Numbers you can plan with)

The Forschungszulage is based on eligible expenditure (in particular personnel costs, but not only).

Funding rates (since 28 March 2024)

  • SMEs: 35%
  • Large enterprises: 25%

Assessment base & maximum values

Important: key dates matter β€” the most common misconceptions arise precisely here.

  • Since 28 March 2024: max. €10M assessment base per year β†’ calculated maximum €3.5M Forschungszulage p.a. (SME) or €2.5M (large enterprise)
  • From 1 January 2026: max. €12M assessment base per year (for expenditure from that date) β†’ calculated maximum €4.2M Forschungszulage p.a. (SME) or €3.0M (large enterprise)

Important from practice: It is not about "the project year" but about the points in time when expenditure is incurred β€” and in some cases also about when the project starts. These key dates are where the most common misconceptions arise (and unnecessarily forfeited funding).

If you want to quickly apply this logic to your own project: Quick check/calculator at dieforschungszulage.de


3) Which costs are eligible β€” and what is frequently overlooked?

In suitable innovation projects, the following types of costs may be relevant, among others:

  • Personnel costs: gross salaries including employer contributions (for employees working on the project)
  • Contract research: claimable at 70% (since 28 March 2024) β€” relevant for external development service providers, specialist laboratories, AI development partners
  • Depreciation: eligible since 28 March 2024 under certain conditions (e.g. for R&D-relevant, movable, depreciable assets, where the individual conditions are met)
  • From 2026: additionally a 20% overhead flat rate β€” but only if the project starts after 31 December 2025 (a strong lever, but not automatically applicable to ongoing projects)

Particularly in software-heavy HealthTech innovations, too little attention is often paid to a clean, auditable allocation: who is working how many hours on which work package β€” and why is it technically uncertain and methodically planned?


4) Which MedTech and HealthTech projects are typically eligible?

In MedTech & HealthTech, the following are frequently eligible (when the innovation core is properly substantiated):

MedTech (classical / hardware-oriented)

  • Development of new implants
  • Development of new materials / surface structures
  • Development of miniaturised sensors
  • New manufacturing or testing processes with technical uncertainty

HealthTech / digital medicine / software / data

  • AI-assisted diagnostics (e.g. image data analysis, signal analysis)
  • Telemedicine platforms and new care workflows (where technically innovative, not merely "implementation")
  • Digital therapy support and patient-centred systems
  • Patient management software with an innovative core (e.g. new decision logic, data-driven models, interoperability solutions)
  • Algorithm development for medical data (incl. robustness, bias reduction, data preparation as part of technical uncertainty)
  • System integration, where it addresses technical risks (e.g. stable interfaces with demonstrable uncertainty/novelty)

What matters is never the label ("AI", "MedTech", "Digital"), but the question: Which technical uncertainty are you resolving systematically β€” and how do you make that demonstrable?


5) What is often not eligible? (Key distinctions in regulated environments)

MedTech/HealthTech is regulated β€” and for that very reason the distinction between "innovation" and "regulatory/administrative work" is crucial.

Typically not certifiable (depending on context and phase):

  • purely routine medical care (application of specialist knowledge without an innovation or development component)
  • regulatory/administrative activities in the context of approval or registration
  • certain clinical study/evaluation phases where they primarily serve approval documentation
  • consulting activities without an innovation core

This does not mean your project is out. However, the application must cleanly demarcate the innovative component and substantiate it technically.


6) Real example: voize β€” €314,825 Forschungszulage for AI-assisted care documentation

One particularly tangible example from the HealthTech space is our case study on voize's AI-assisted care documentation: €314,825 in funding was secured for the project. To the voize case study

Why is this so typical of eligible software innovation?

  • Documentation in care is a real time and quality lever
  • The solution is not "just dictation" but requires structured processing, integration into existing systems, and validation in everyday use
  • The effort lies in iterations, stabilisation, testing, quality assurance, and interface work β€” precisely the patterns that the Forschungszulage addresses

If you yourself are working on AI or process software in healthcare: such projects are often eligible β€” if the innovation core is described and documented in a technically rigorous way.


7) How to use the Forschungszulage strategically in MedTech/HealthTech projects

In practice, applications work particularly well when you consistently do three things:

  1. Define the project scope clearly What is genuinely innovation/development (technical uncertainty, methodical approach) β€” and what is product maintenance, implementation, or regulatory work?

  2. Describe technical uncertainty concretely Not "we are building AI", but for example: which data problems, performance limits, robustness questions, integration risks are being solved?

  3. Think "eligible" from the start when documenting Work packages, objectives, approaches, tests, results, iterations β€” traceable and auditable.

You can find an overview of the process here: Application process at dieforschungszulage.de


8) Why this article matters (and what you should take away)

In practice, maximum funding rarely fails because of the degree of innovation β€” it fails because of key dates, caps, and an inadequately documented scope definition. If you apply the rules correctly (28 March 2024 vs. 1 January 2026) and present innovation methodically, the Forschungszulage transforms from a "bureaucracy topic" into a genuine cash flow instrument.

Official starting point (important for orientation): Bescheinigungsstelle Forschungszulage (BSFZ)


9) Conclusion: Forschungszulage is the predictable innovation lever for MedTech & HealthTech

If you are developing in MedTech or HealthTech β€” whether a medical device, algorithm, data platform, AI application, or digital care solution β€” a structured look at the Forschungszulage is almost always worthwhile.

If you would like, we can assess this together in a free funding check β€” and tell you clearly which rules apply to you (28 March 2024 vs. 1 January 2026) and how to align your project optimally with the Forschungszulage. Free funding check at dieforschungszulage.de


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