AI app for science and research · no coding needed
Peer-review response evidence planner
Every response tied to an actual manuscript change or stated rationale.
Made for: Academic authors revising manuscripts

What it does for you
The problem
Response letters lose track of which changes address each comment.
What it gives you
Coauthor-approved review response pack
What you give it
Authorized reviewer commentsmanuscript versions
How it works, step by step
- Separate reviewer requests
- Link manuscript changes
- Flag unanswered points
- Draft factual responses
- Track coauthor approval
- Export response letters
What you see on screen
- Comment matrix
- Revision evidence
- Response draft
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 Peer-review response evidence planner 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 Peer-review response evidence planner 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 Cloudflare25 KB
- prompt-vps.mdThe same build on your own server (Docker)25 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria14 KB
- demo/index.htmlThe working demo on sample data198 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 academic authors revising manuscripts, turn authorized reviewer comments and manuscript versions into coauthor-approved review response pack. Address this specific problem: response letters lose track of which changes address each comment. The aim: every response tied to an actual manuscript change or stated rationale. The pilot tests whether that benefit holds up against reviewer effort and real operating costs.
The buyer creates a project, supplies authorized reviewer comments and manuscript versions, and confirms scope and access. Users correct extracted facts, resolve flagged uncertainties and approve the final coauthor-approved review response pack before use. Retain source links and a version history for the next cycle.
How the AI works
Draft responses from documented revisions only. Keep model suggestions separate from verified facts. Link factual outputs to authorized input evidence and show missing information explicitly. Use deterministic checks for counts, dates, identifiers and arithmetic where applicable. A designated reviewer validates consequential outputs and signs off the delivered result.
Safeguards
Preserve original data, methods, citations and research limitations. Use researcher review and document every substantive transformation. No fabricated analyses or claims of changes not made. Require appropriate access and publication approval. Preserve source material, label AI drafts and make corrections traceable. Measure false positives and missed cases alongside speed.
What to build first
Costed pilot: No fabricated analyses or claims of changes not made. Start with one buyer organization and a bounded set of representative inputs. Implement the first two modules: separate reviewer requests; link manuscript changes. Support the third task through an assisted review queue: flag unanswered points. Handle the remaining required functions manually until validated. Include input upload, source references, user correction, a reviewer approval step and export of coauthor-approved review response pack. Authentication, account isolation, deletion controls and basic operational logging are included. Specialized production certification, live write integrations and broader rollout are not included unless explicitly stated.
What it can connect to
Authorized datasets, papers, protocols, code and research records. Document storage, word processor export, content management systems and approved publishing channels. Pilot with uploads and downloadable drafts before adding write integrations. Begin with uploads and exports of authorized reviewer comments and manuscript versions. Any named system or connector is a candidate requiring current access and compatibility checks; no live connection is included by default.
The screens in detail
Use a project list and editorial calendar beside a document editor. Keep original material and supporting passages in a collapsible side panel. Show outline, draft, review and approved stages. Provide tracked edits, comments, version comparisons and an export preview that reflects the final delivery format. Open with comment matrix; move into revision evidence for the detailed task; finish in response draft for review and handoff. Show the source record, uncertainty and approval status beside each proposed output.





