Today, many development ideas start with the promise that they will include artificial intelligence. It sounds good, but on its own, it is not enough. Connecting an AI API, building a dashboard, or using an existing model does not automatically make a project research and development.
In DIMOP Plusz schemes, the key is to demonstrate whether the project has a genuine technological core: a new algorithm, a proprietary data processing method, a new logical model, non-trivial system integration, or a technical uncertainty that cannot be solved through routine development.
Not every modern software project is R&D
In modern software, an API layer, access management, a database, automated deployment, reporting, and often some form of AI component are now standard. On their own, these are usually good software development practices, not R&D results.
From a grant evaluation perspective, the crucial question is which part of the development cannot be bought off the shelf, imported from open source, or solved through standard integration. Without a strong answer to this, the project may still be commercially useful, but it may not be defensible as digital R&D.
What makes software development R&D?
Software development can be considered R&D when the project creates new technological knowledge and involves uncertainty that must be resolved through systematic development work.
This may include, for example, a proprietary algorithm, a domain-specific AI model, a data processing pipeline, a real-time decision-support engine, a machine learning solution running in an edge environment, or a new cybersecurity method.
A new admin interface, report, chatbot, or access level is rarely sufficient on its own. The situation is different if the development creates reliable decision support from noisy data, builds a real-time data model from multiple systems, or makes AI-based decisions explainable and auditable.
STEP alignment: strategic technology focus
STEP alignment is also important in DIMOP Plusz applications. This means that the project must not only be digital, but also connected to a strategically significant technology area. Examples include AI, data analytics, cloud, edge, IoT, cybersecurity, digital identity, autonomous systems, robotics, healthtech, or defence tech.
A strong project is not just an idea, but it is also not the simple resale of an already finished product. It has a technological foundation, while still containing meaningful development uncertainty, validation work, or scaling challenges.
For more information or consulting, please fill in our contact form.