For universities & research institutionsMORE RESEARCH,LESS PAPERWORK
A small grants team facing hundreds of researchers, and calls that hit everyone at once. Researchers write applications on top of their research and teaching, and the support team cannot possibly go equally deep into everything.
Twin gives researchers structure and writing support, while the grants office keeps control and the quality standard. Set up for a public institution: data in the EU, verifiable, and no training on your data.
Everyday practice
The dilemma of research support: helping everyone at once, while being able to account for how that happens.
Clustered deadlines, small team
“At every call deadline the same small team faces a hundred researchers.”
Researchers get a long way on their own: the platform guards structure, completeness and the requirements of the call, and co-applicants deliver their CVs, budgets and letters of support where they belong. The grants office keeps its hours for the applications where guidance pays off most.
AI use must be explainable
“Using AI is allowed, but then I need to be able to explain how.”
Funders and institutions set requirements for AI use. Twin makes it explainable: which source, which step, which check. EU-hosted, no training on your data, and, if you wish, a language model that stays entirely within the EU.
Sensitive research data
“Pre-publication research ideas don't belong in a public tool.”
Ideas, preliminary data and strategic collaborations stay within the institution's environment. Multi-tenant isolation, encryption, and a DPA the privacy officer can stand behind.
One journey, one knowledge layer
Today Twin supports the application process, from opportunity to submission. We are now building out the phase after the award (obligations, reporting, accountability); the file from the application phase will be the basis for it.
When the funder asks how AI was used
More and more funders ask for transparency about AI use in applications. Twin is built so that you have that answer.
Which source
Every passage is traceable to the source it is based on. Anything that does not come from a source is flagged.
Which step
The audit trail records which AI steps were taken, when, and based on which input. Available whenever the institution or the funder asks for it.
Which check
Review and approval are part of the process: the researcher and the grants office have the final say over every text.
How it fits a public institution
Researchers stay in control
Twin does not write the research, it helps the researcher structure their own story and test it against the requirements of the call. The idea remains the scientist's.
Set up for public accountability
Audit trail as standard, source reference per passage, and documentation for the institution's privacy and security review.
Reusable institutional knowledge
Successful applications and review insights become reusable knowledge for the next call, within the institution and where needed restricted per team.