Why Generative AI isn’t enough for grant writing
By Theodoor Rutgers, Founder and CEO of Grantific
There was no single lightbulb moment behind Grantific
The idea grew out of something we experienced first hand at Catalyze. For more than twenty years, we have helped organisations secure public funding. As an expert consultancy, we understand how much knowledge, documentation and coordination goes into developing a successful grant proposal. The process is complex, knowledge-intensive and time-consuming. We always kept asking ourselves: can technology help us do this better?
When generative AI became widely available, we were excited by the possibilities. But after testing many solutions, it became clear that generic AI is not built for this type of work.
Grant applications require a deep understanding of complex documentation, strict evaluation criteria and complete traceability. They are too important to rely on technology that occasionally hallucinates or cannot explain where information comes from.
That was when we stopped looking for a tool that could simply help write and started looking for a fundamentally different approach.
Choosing to build the right product
The strongest argument against starting Grantific was that it would have been much easier not to.
Building an AI company in today’s market requires significant investment, patience and conviction. There is enormous hype, new tools appear every week, and many people assume that another layer around a generic language model is enough.
We believe the grant industry needs a tool that really understands the grantwriting process.
Grants often determine whether important innovations are funded, delayed or never reach the market at all. That deserves a higher standard than fluent, automatically generated text.
Instead of building the fastest product, we chose to build the right one, combining proven AI technology with decades of grant expertise.
Bringing grant expertise and AI together
When we met Brainial, we immediately recognised that its technology was fundamentally different. Rather than focusing on text generation, Brainial had developed an AI architecture capable of understanding and structuring large collections of complex documents. It had already been applied to more than 70,000 enterprise tenders.
That was exactly what grant writing needed.
Catalyze brought more than twenty years of grant-domain knowledge. Brainial brought proven AI technology for complex, document-intensive processes. Both companies operate in fields where quality, accuracy and trust matter more than speed alone. Both also believe that technology should support professionals, not replace them.
Together, we could build something neither company could have created independently.
When funding becomes a barrier to innovation
Founders do not start companies because they enjoy writing grant proposals. They start them to build technologies, validate products and create impact.
Yet many spend weeks or even months collecting documents, interpreting funding requirements and rewriting the same information for different programmes. Every hour spent searching through documentation or formatting an application is an hour not spent developing a product, speaking with customers or growing a business.
The consequences can be significant. We have seen promising innovations delayed, and sometimes abandoned, because teams lacked the capacity, experience or resources to navigate increasingly complex funding programmes.
Funding is never the only reason a company succeeds or fails. But the funding process should accelerate innovation, not become a barrier to it.
Our goal is not to remove people from the process. It is to remove repetitive work, simplify grant writing and make funding more accessible, so researchers and innovators can spend more time advancing their ideas.
What the AI hype gets wrong
Much of the current AI hype rests on the assumption that adding a chatbot or generating fluent text is enough to solve a complex business problem.
Many tools look impressive in a demonstration, but remain generic underneath. They can produce convincing answers without truly understanding the domain, the workflow or the context in which professionals operate. This can encourage users to place too much trust in outputs without being able to assess their accuracy, relevance or source.
In a high-stakes field such as grant writing, that is not enough. People need reliable answers, transparency and control. They need to understand why an AI system produced a particular output and where the underlying information came from.
AI should increase trust, not replace it. It should support human judgement rather than ask users to accept fluent language at face value.
“I believe this is the future of AI”
Successful grant writing involves much more than writing. It requires identifying the right opportunity, interpreting call documentation, coordinating stakeholders, managing knowledge, aligning with evaluation criteria, developing work packages and budgets, and collaborating throughout the process.
That is why we built Grantific as more than an AI writing assistant. It is a collaborative platform for the entire grant lifecycle, combining domain-specific AI with structured workflows, knowledge management, secure collaboration and expert guidance.
The platform works with structured knowledge, connects outputs to their sources and allows users to remain in control of the information being used. Every feature is designed specifically for grants, from funding discovery and proposal development to partner collaboration.
I believe this is where the future of AI lies, not in building one generic tool that tries to do everything, but in creating technology that understands one domain exceptionally well.
