AI app for science and research · no coding needed
Grant opportunity matching
Eligibility and collaboration requirements are explicit alongside topic fit.
Made for: University research support offices
What it does for you
The problem
Researchers miss suitable calls or pursue ineligible ones.
What it gives you
Research funding shortlist
What you give it
Published funding callsresearcher-declared project profiles
How it works, step by step
- Match research themes
- Extract eligibility
- Compare institution constraints
- Identify partner requirements
- Track call revisions
- Save pursuit decisions
What you see on screen
- Funding watchlist
- eligibility evidence
- deadline calendar
Build it yourself with your AI system
Build this app yourself, no coding needed
Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.
Sign in to see how to build it yourself
Build a quick version to try, or get the full app pack for Grant opportunity matching with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.
4 Have it built for you days to a few weeks
Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Grant opportunity matching with you.
What's in the app pack
Included in the Complete AI Training membership.
- The building instructions your AI follows, step by step
- The questions your AI will ask you about your business before it starts
- A clickable demo you can open in your browser, to see how it should work
- A detailed blueprint of the screens, the information it keeps and the checks it runs
Become a member to get the app packAlready a member? Sign in
The files, for the technically curious
- START-HERE.mdHow to build it with your own AI (read first)3 KB
- README.mdOverview and links1 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare22 KB
- prompt-vps.mdThe same build on your own server (Docker)22 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria12 KB
- demo/index.htmlThe working demo on sample data202 KB
Questions
Do I need to know how to code?
No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.
What does it cost?
The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.
How long does it take?
The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.
Can I change it to fit my business?
Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.
More detailsHow the AI works, safeguards and what to build first
For university research support offices, turn published funding calls and researcher-declared project profiles into research funding shortlist. Address the recurring problem: researchers miss suitable calls or pursue ineligible ones. The pilot measures eligible match rate and useful opportunities against the buyer's current method, before the larger build.
Define buyer-selected criteria, gather authorized opportunity information, apply explicit eligibility rules, propose matches with evidence, let the user review uncertain conditions, save a shortlist and track the resulting conversations or applications. Start with published funding calls and researcher-declared project profiles and finish with research funding shortlist.
How the AI works
Extract criteria, normalize opportunity descriptions and explain possible fit. Use explicit rules for hard requirements. Do not invent missing eligibility facts or represent a suggested match as a verified qualification.
Safeguards
Preserve original data, methods, citations and research limitations. Use researcher review and document every substantive transformation. Validate source access and reviewer availability during the pilot. Maintain customer-level access, data deletion controls and a record of final approvals.
What to build first
Begin with university research support offices and one recurring use case. Build the first two modules: match research themes; extract eligibility. Provide operator assistance for the third module: compare institution constraints. Deliver research funding shortlist through a manual review queue. Perform other necessary full-scope functions manually during the pilot. Include all applicable access, accuracy and professional-review controls from the start.
What it can connect to
Authorized datasets, papers, protocols, code and research records. Permitted opportunity feeds, customer profiles, calendars and CRM exports. Keep initial outreach or applications as user-reviewed drafts. These are candidate integration categories, not verified supported connectors.
The screens in detail
Open with a filterable opportunity feed and clear fit explanations. Each profile shows source evidence, eligibility conditions and missing information. Keep saved, rejected and needs-review states. Include a deadline or next-action view without hiding the basis of recommendations. In this product, the first view is funding watchlist, followed by eligibility evidence and deadline calendar.
