Write better grant proposals

Impacter supports you while you write
to deliver the best grant possible.

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Checking the ingredients

Make sure you covered all the bases

Did you address all of the things needed for a good Impacter chapter? Impacter checks your document against a list of ingredients, compiled out of 600 existing proposals.


How does your research compare to other proposals?

Impacter runs a document similarity algorithm that compares your proposal to a combined database. The databases include CORDIS, NARCIS, RVO, FRIS, SweCRIS the UKRI and NSF. We make copies of these databases, so your document does not leave our server.

For an increasing number of funding bodies, these analyses are also provided to reviewers to ensure that funded projects are sufficiently distinctive.

Word comments

Directly continue writing

Comments based on the semantics of your writing are given back to you, in your original proposal! This means you can pick up where you left off, and address the comments while you write.

Spend more time on content

Because regular feedback is taken care of.

In the busy time towards a deadline, you want to spend your scarce time where it matters. Impacter tackles the common issues and style elements, making sure that when you get the text, frequent pitfalls have been addressed.

Grant matching

Who should write for which opportunity?

Impacter uses Document Similarity technologies to identify the best links between a researchers publication history (from the public repository) and funding opportunities. We help you to:

  • Find the publication profiles matching a EU topic
  • Find the publication profiles matching a custom topic text
  • Find the topics best for a specific researcher
  • Insight and Analytics beta

    Quantify insights in proposals

    At an aggregate level, a lot of insights can be gathered from proposals and the linked databases. Think of the following:

  • Specific research organisations that your institutions' proposals align with
  • Organisations mentioned in proposals of your researchers.
  • The routes towards creating Impact that your researchers prefer.
  • Aggregate scores to find latent training needs.

  • Active users

    Calls supported


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    Meet the team

    Impacter is a startup company located in Utrecht.

    Tijmen Altena Chief Technology Officer
    Martijn van Beers Data Scientist
    Peter Lombaers Machine Learning Engineer
    Ana Rodrigues Customer Success Manager
    Paul Tuinenburg Chief Executive Officer

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    Start using Impacter today for your national and European research grant applications.

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    Maximize your institutions' success rate.

    Start using Impacter today for your national and European research grant applications.

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