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AI Assistant for Academics

Literature review taking 5 days? Ryna AI Plus brings it to 5 hours. Paper drafting, reviewer responses, grant proposals, student paper grading.

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Ryna AI Editorial Team · Updated 04.03.2026

Academic life is a time-scarcity problem: between teaching loads, project reports, review invitations and admin, the hours left for actual research keep shrinking. Yet a single systematic review takes, on average, more than a year from registration to publication (Borah et al., BMJ Open 2017 — median ~67 weeks). Screening hundreds of papers into a synthesis, drafting an abstract, answering reviewer comments, polishing grant text — all of it has to fit the same calendar.

Ryna AI takes over the 'mechanical' part of that workload and frees you to think. Upload the PDFs you already have (Plus) and get a theme-by-theme synthesis, draft a structured abstract in IMRaD form, build a non-defensive point-by-point reply to Reviewer 2, or strengthen the 'significance' and 'broader impacts' sections of an NIH/NSF/ERC/Horizon proposal. Critical caveat: never expect Ryna to invent a bibliography or citations — language models can produce realistic-looking but non-existent DOIs and references; you must verify every citation yourself in Google Scholar, Scopus, Web of Science or a DOI resolver. The safest workflow is to upload the real PDFs you hold and work on the actual text.

Treat Ryna as a drafting and thinking partner, not a 'paper writer': you supply the context, it returns a skeleton for you to work on, and the final scientific content and responsibility stay yours. On the free plan you can paste text and work with near-unlimited daily messages; upgrade to Plus (399.99 TRY/mo) for PDF/file analysis, deep thinking and web research.

Why use Ryna AI for this

Literature synthesis: collapse the PDFs you upload (Plus) into one thematic table by shared findings, conflicting results and gaps — 20 papers on a single page.

Abstract drafting: a structured or IMRaD-format draft shaped to the journal's word limit (150/250 words) and citation style.

Reviewer response letter: a respectful, non-defensive point-by-point skeleton with 'accept / partially accept / politely push back' tags for each comment.

Academic language polish: turn your own draft into academic English a native reviewer finds natural, fixing recurring article/preposition/tone issues.

Grant and proposal text: persuasive, clear draft suggestions for the significance, methods, work packages and broader-impact sections (NIH/NSF/ERC/Horizon).

Support tasks in one chat: a cover letter to the editor, journal-fit reasoning, a plain-language summary, and writing up a review you are doing in firm-but-courteous language.

Example prompts

Copy any prompt below and paste into chat.rynaai.com. Each prompt is tuned for a different scenario — try them all to see how Ryna AI adapts.

>Read these 8 PDFs I uploaded. Build a thematic synthesis table around shared findings, conflicting results and the gap in the literature; on each row note which paper it came from, and use only information from the documents.
>From the following results and methods summary, write a 250-word structured abstract (Objective, Methods, Results, Conclusion); add no new findings, use only the data I gave: [text]
>Reviewer 2 wrote: 'Sample is small and generalizability is weak.' Draft a non-defensive, constructive point-by-point reply; separate where I'll revise from where I'll politely push back.
>Translate this paragraph into academic English, then make it read naturally to a native reviewer; do not change the meaning or terminology: [paragraph]
>Draft the 'significance/innovation' section for an NIH R01: topic [X], gap in the literature [Y], our contribution [Z]. 400 words, clear enough to convince the panel.
>Write a cover letter to the editor: paper title [...], why it fits the journal's scope, 3 main contributions. 200 words, formal and concise.

How it works — step by step

  1. 1

    Give context and the task

    Open chat.rynaai.com and state clearly what you're doing: abstract draft, reviewer response, or literature synthesis? Specify discipline, target journal, language and word limit. If you have the PDFs, upload them (Plus) — the model reads the real text, which sharply lowers fabrication risk.

  2. 2

    Set the constraints

    Add the instruction: 'Use only information in the text I uploaded/pasted, add no outside sources, and flag anything you're unsure of as uncertain.' That single sentence substantially reduces hallucinated claims and invented citations.

  3. 3

    Get the draft and verify sources

    Look up every citation and DOI Ryna gives you in Google Scholar, Scopus or Web of Science yourself; delete anything that doesn't match. This step is not optional — fake references are the fastest thing editors and reviewers catch.

  4. 4

    Iterate in your own words

    Feed the abstract, discussion or response draft back with your own phrasing: 'Replace the results sentence with mine' or 'the Action part is weak, add a quantitative result'. The text gradually becomes your voice.

Example: input → output

You ask

Reviewer 2 comment: 'The sample is limited to 42 participants, findings are not generalizable. There is also no control group.' Write a non-defensive, point-by-point reply draft.

Ryna AI returns

**Response to Reviewer 2 (draft — fill in your own page/line numbers)** We thank the reviewer for their constructive feedback. We address each comment point by point below; the corresponding changes are marked in the revised manuscript. **Comment 1 — Sample size (n=42) and generalizability. → We partially agree.** You raise a fair point. We have positioned the study as an exploratory pilot and now state this explicitly at the end of the Introduction and in the Limitations section (see p. X, line Y). We justify the sample size with a post-hoc power analysis (achieved power = [VALUE], effect size d = [VALUE]). We have softened the generalizability claim, reframed the results as 'preliminary findings', and added a larger-sample confirmatory study as future work. **Comment 2 — Absence of a control group. → We respectfully clarify.** Our design is a single-group pre-post test, so there is no classical control group; we have added the rationale for this choice (ethical and sampling constraints) to the Methods (see p. X). To offset this limitation we applied within-subject comparison and baseline correction, and we discuss the potential bias transparently in the Limitations. We believe these revisions strengthen the paper's contribution and would be glad to address any further requests. [Note: Fill the power-analysis and effect-size values with your real data — Ryna only inserted placeholders here. Update the page/line references against your revised file.]

Pro tips

  • Safest workflow: upload the real PDFs before asking for a summary or synthesis (Plus). The model quotes from the text instead of 'recalling' from memory — this kills most of the fabricated-finding and fake-reference risk.
  • For an abstract, paste the bare results sentences first, then say 'compress these into 250 words'. Without raw material, the model may fill gaps with invented numbers.
  • In a reviewer reply, tag each item 'Accept / Partially accept / Politely push back' and leave page-line placeholders for your revisions; it's easier for the editor to read, and you fill in the real numbers after.
  • Use deep-thinking mode (Plus) to structure the discussion's argument and to surface counter-arguments a reviewer might raise — you harden your defense before you even submit.
  • Use paraphrasing to simplify your own first draft, not to launder plagiarism. Re-wording someone else's text is an integrity violation, doesn't beat similarity checkers, and increasingly gets caught by AI detectors too.
  • Even when web research (Plus) returns real links, open each source and confirm the claim actually appears there; the model sometimes attaches the wrong sentence to the right link.

Common mistakes to avoid

  • Dropping Ryna's bibliography into the paper without checking it — fake or wrong DOIs are the fastest thing editors and reviewers catch.
  • Saying 'summarize the latest 10 papers on X' without uploading PDFs — with no real text in front of it the model may invent from memory; either give the PDFs or open each web-research (Plus) link yourself.
  • Having the model write the whole text and presenting it as your own original work — it's an integrity violation, breaks journal/institution policy, and is increasingly detectable.
  • Asking for a draft without stating the journal's rules (word limit, abstract format, citation style, language) — you'll end up rewriting from scratch.
  • Sending a defensive or emotional reply to a reviewer — unless you ask for a 'constructive, neutral tone' the model can come out too assertive; soften it before it goes out.

Who this is for

Assistant to full professors, PhD students, post-docs.

FAQ

If Ryna writes my paper for me, is that plagiarism / an integrity violation?

Having it generate the whole text and passing it off as your own original work, making it invent sources, or having it re-word someone else's text and claiming it — those are violations. Ethical use is: literature-search help, language and structure polish of your own draft, an abstract skeleton, a reviewer-response draft. Most journals and institutions (COPE, and university policies) require AI use to be disclosed in the methods or acknowledgements — check your institution's and the journal's policy. Final authorship and responsibility are always yours.

Why do I have to verify the citations and DOIs myself?

Because language models can produce realistic-looking but non-existent references and DOIs. Verify every citation yourself in Google Scholar, Scopus, Web of Science or a DOI resolver. The safest approach is to upload the real PDFs you already have (Plus) and work from the actual text.

Can I submit the abstract it produces directly?

Take it as a draft and match it line-by-line to your real findings. The model sometimes 'embellishes' numbers, effect sizes or conclusion statements; confirm every sentence agrees with your data before you use it.

Does it do reviewer-level language editing for an English paper?

It's quite strong on grammar, fluency and tone, and catches recurring non-native patterns well. Still, leave field-specific terminology and the final read to a native expert editor. Some journals require AI language editing to be disclosed too — check first.

How much can I do on the free plan?

Anything you paste as text — abstract drafts, reviewer responses, paraphrasing, translation, grant text — works on the free plan with near-unlimited daily messages. PDF/file analysis, web research and deep thinking require Plus (399.99 TRY/mo).

Related use cases

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