AI & Workflow Automation
AI & WORKFLOW AUTOMATION
AI where it earns its place, and nowhere else
Screening, reviewer matching, metadata extraction and language support — applied to the repetitive parts of publishing, with editorial judgement left entirely to your editors and confidentiality protected end to end.
Submissions are rising. Your editorial team isn’t.
Volume is up across almost every journal, and paper mills have made screening harder at exactly the moment desks are most stretched. Meanwhile the same editor is still reading forty submissions to reject twelve on scope, retyping author affiliations into a metadata form, and searching for a reviewer who works in a subfield they don’t.
AI is genuinely good at those jobs. It is not good at deciding whether a paper should be published. We build systems that respect the difference.
What we build
Submission screening
Automated checks for scope fit, structure, reference integrity, missing sections and formatting — surfaced as a flagged summary for your editor, not a decision.
Integrity signals
Similarity checks, reference-pattern anomalies, image reuse flags and paper-mill indicators, routed to a human for review with the evidence attached.
Reviewer matching
Candidate reviewers ranked by subject fit, publication history and availability, with conflicts of interest flagged before the invitation goes out.
Metadata extraction
Authors, affiliations, ORCIDs, funding statements and references pulled from the manuscript automatically, then validated against your records.
Language support
Readability and grammar suggestions for authors writing in a second language, offered as revisions they choose to accept — never applied silently.
Editorial assistance
Draft decision letters, reviewer report summaries and status updates prepared for your editors to edit, approve and send.
What we will not build
The limits matter more than the features. These are fixed, not negotiable per project.
No AI acceptance or rejection decisions
Every screening output is a flag with reasoning attached, reviewed by a person. The editorial call stays with your board, always.
No AI peer review
A model does not replace a reviewer, and we won’t build something that pretends otherwise.
No manuscripts sent to public models
Unpublished work is confidential. Processing runs on infrastructure with no training retention, under contractual terms we’ll show you.
No AI-generated research content
We do not write papers, abstracts or results, and we help you detect submissions that were.
No black boxes
Every automated flag is explainable and logged. If you can’t tell an author why something was flagged, the system has failed.
This aligns with COPE and industry guidance on AI in publishing. If a vendor offers you AI that decides, reviews or writes, that’s a reason to walk away — from them, and from us if we ever drift.
How it works
1
Discovery call
We look at where your editorial time actually goes and identify which steps are genuinely automatable and which need a human. You get the honest split, including the parts we’d advise against automating.
2
Build and validate
Systems built into your existing workflow and tested against your own historical submissions, so you can see accuracy on real data before anything goes live.
3
Deploy and monitor
Rolled out with a human in the loop from day one, with accuracy monitored, thresholds tuned and a named contact for support.
Tested on our own desk first
Amplionix operates its own peer-reviewed open access journals. Every screening rule and matching model here was run against our own submission queue before it was offered to anyone else — including the versions that didn’t work and got cut.
That’s also why the guardrails above are specific rather than decorative. We’ve seen what over-automating an editorial desk does to a journal’s reputation, and it isn’t recoverable.
12+ years
running editorial desks, not just building for them
Human in the loop
on every decision point, by design
Validated on your data
before go-live, with accuracy reported
Full audit trail
on every automated flag
Fixed build, flat monthly
Automation work is quoted as a fixed-scope build against your workflow, followed by a flat monthly plan covering hosting, monitoring, model updates and support. No per-manuscript fees. You’ll have the number before development starts.
FAQ
No. Screening produces flags and a summary; a person decides. We’d refuse to build it the other way round.
Onto infrastructure we configure for you, under terms with no training retention. Unpublished submissions are never sent to public consumer AI tools, and we’ll document the exact data path in writing.
We validate against your own historical submissions and report real numbers before launch. Any vendor quoting a headline accuracy figure without seeing your data is guessing.
Yes. Every check is independently configurable, and thresholds are yours to set.
Not when it’s disclosed and confined to editorial support rather than decisions or peer review. We help you write the AI use policy that goes on your site.
Start with an honest assessment
One call, no obligation. We’ll tell you which parts of your editorial workflow AI can genuinely help with — and which parts it shouldn’t touch.
Or email us at kushal@amplionix.com
Want the wider back office automated? Publishing Operations → · Need the platform itself built? Publishing Technology → · Want us to run the journal? Journal Management →