Research Automation
AI Research Reviewer
AI Research Reviewer is a live web application for pre-submission manuscript review. Researchers can submit manuscripts, track review progress, review generated feedback, and use structured reports to improve quality before formal journal, conference, supervisor, or internal review.
Founder-builtLive research toolPre-submission review automation
Value Story
Research review built for submission confidence.
Authors need useful feedback before submission
Researchers often submit papers without enough structured review, creating avoidable revision cycles and unclear improvement priorities.
AI feedback shaped like reviewer concerns
The product converts uploaded manuscripts into organized review signals, concern areas, and practical author-facing reports.
Better preparation for journals and supervisors
The workflow helps authors, students, and research teams improve clarity before journal, conference, or supervisor review.
My Contribution
From research workflow to live review product.
Defined the product positioning as a pre-submission manuscript review assistant.
Designed the submission, review-history, dashboard, notifications, and report-review workflows.
Created safety and terms language around AI-generated research feedback and manuscript handling.
Deployed the application as a live product with public access at reviewer.plenware.cloud.
Product Capabilities
What the user actually gets
Manuscript review
Uploaded papers are analyzed for structure, clarity, contribution, and improvement opportunities.
Reviewer concerns
Feedback is framed around the type of issues reviewers and supervisors are likely to notice.
Review history
Users can return to previous review sessions and compare feedback across manuscript iterations.
Downloadable reports
Structured reports turn AI analysis into a practical artifact authors can use during revision.
System Architecture
Manuscript to review report flow
Public landing and authentication layer introduces the service and manages account access.
Submission workflow captures manuscript materials and metadata for automated review.
Processing layer generates structured review feedback, recommendation signals, and quality scores.
Workspace layer supports dashboard, analytics, profile, help docs, notifications, and review history.
Report layer presents completed review output and supports researcher follow-up actions.
Outcomes
What this proves
- Launched a publicly accessible AI research review product.
- Created a practical workflow for manuscript submission, review tracking, and generated feedback.
- Strengthened the portfolio with a live tool that visitors can open and use.
- Demonstrated applied AI product thinking across research, UX, safety language, and deployment.
Technology
Core stack
Next.jsReactAI Review WorkflowsReport Generation
Work together
Need an AI product that turns expert review into usable feedback?
I can help design the review logic, user workflow, reporting layer, and deployment path for research or knowledge-work products.
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