AI app for science and research · no coding needed
Research collaboration discovery
Method-level complementarity supported by specific published work.
Made for: R&D groups seeking complementary expertise
What it does for you
The problem
Potential collaborators are identified from incomplete informal networks.
What it gives you
Collaboration research briefs
What you give it
Published workdeclared project needscollaboration criteria
How it works, step by step
- Define capability gaps
- Identify relevant teams
- Cite supporting publications
- Compare complementary methods
- Flag outdated affiliations
- Prepare collaboration concepts
What you see on screen
- Expertise map
- team profiles
- fit evidence
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 Research collaboration discovery 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 Research collaboration discovery 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 build3 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 data193 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 r&D groups seeking complementary expertise, turn published work, declared project needs and collaboration criteria into collaboration research briefs. Address the recurring problem: potential collaborators are identified from incomplete informal networks. The pilot measures verified relevance and useful introductions 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 work, declared project needs and collaboration criteria and finish with collaboration research briefs.
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 r&D groups seeking complementary expertise and one recurring use case. Build the first two modules: define capability gaps; identify relevant teams. Provide operator assistance for the third module: cite supporting publications. Deliver collaboration research briefs 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 expertise map, followed by team profiles and fit evidence.
