Every rule.
38 checks per journal, run on every line. From heading order to reference style, nothing in your submission rides on luck.
Seven review agents read your manuscript against your target journal's own rules and hand back native Word tracked changes, every one cited. You accept or reject each, inside Word.
Waraq reads your manuscript like the harshest reviewer, then hands you every fix as real Word tracked changes. In minutes, not months.
Every fix, as real Word edits.
Every change cites a real rule.
Reviewed while your coffee's hot.
Reviewed against your target journal.
Still your words, still your paper.
Built to get past the desk.
Not a chat transcript. A reviewed file with tracked changes you accept or reject inside Word, findings cited to your journal's rules, a score you can defend, and a reviewer you can question.
The results suggest the intervention was very effective associated with a 23% improvement across all cohorts, although attrition in the control group was not fully reported is reported in Table S2.
Quantify the effect size; replace the qualitative claim.
Report attrition for every arm. Now cited to Table S2.
Ready to resubmit after 14 accepted changes.
Why flag the attrition sentence?
PRISMA 2020 §17 asks for attrition reported in every arm. Your counts already exist in Table S2, so the revision cites them and the journal's reviewer never has to go looking.
PRISMA 2020 · §17A Waraq review is not one model's opinion. Seven specialised agents run on your manuscript in sequence, each with one job, each writing its edits and citations into the same tracked-changes file.
One file back · every edit signed by the agent that made it
Three short films from the review desk. Every rule checked, every rejection headed off, every minute accounted for.
38 checks per journal, run on every line. From heading order to reference style, nothing in your submission rides on luck.
Most desk rejections are never explained. Waraq finds the trigger, cites the rule behind it, and fixes it before an editor ever sees your file.
A full seven-agent review at a median of four minutes, returned as tracked changes while your coffee is still hot.
Waraq is trained on the published rules of over fifteen thousand journals. Paste your abstract or a topic, and it ranks the ones that actually fit, then reviews your paper against the winner's exact guidelines.
Every match is scored against the journal's real scope, method preferences, and formatting rules, not a keyword guess. Pick one, and the review runs against its exact guidelines.
While you work, the Research Agent reads what publishes in your field, flags the questions nobody has answered, ranks the journals that would want the answer, and hands your draft straight to the seven-agent review.
No study pairs this method with your population.
One plan, two review modes. A fast Desk Review to screen a clean draft, a deep Peer Review when the argument needs a senior reader. Less than one submission fee.
The desk editor's first screen. Formatting, citation style, structure, and reference completeness against your target journal, returned as tracked changes in seconds.
A senior reviewer's read. Argument, evidence, method soundness, and the gaps that trigger a revise or reject, each point cited to a rule. Our best AI models, for the papers that matter.
It reads the draft first: a Desk Review for a clean paper, a Peer Review when the argument needs work. You spend your deep reviews only where they count.
How it works: a Desk Review is a quick pass, a Peer Review is a full read. Your plan includes both and refills automatically.
Waraq edits your writing. It does not write for you. Upload your paper and see results in minutes.