Inspiration
As a graduate student and early-career professional, I grew frustrated with generic grammar checkers that missed structural and tonal issues in academic papers and workplace docs. I wanted a tool that didn’t just fix errors—but taught users to write better, tailored to their audience.
What it does
WritingFeedback AI analyzes text across 5 core dimensions (grammar, structure, logic, tone, readability) to deliver actionable, sentence-level revisions. It adapts feedback for academic/professional/general audiences, tracks progress, and detects plagiarism—with free/premium tiers for accessibility.
How we built it
I built the frontend with React for a intuitive 3-panel interface, used Python/Node.js for backend logic, and leveraged AWS for scalable processing. I integrated NLP and readability APIs to power analysis, PostgreSQL for user data/history, and Chart.js for the premium dashboard’s progress visualizations.
Challenges we ran into
Balancing fast analysis (3-5s) with deep multi-dimensional checks was tough—optimizing API calls and reducing processing latency required iterative testing. Also, tailoring feedback logic for 8+ audience subtypes meant refining AI prompt engineering to avoid generic suggestions.
Accomplishments that we're proud of
Creating a tool that’s both functional and educational—users don’t just get revisions, but explanations to build skills. The premium dashboard’s progress tracking has helped early users identify recurring mistakes and improve scores by 20% on average.
What we learned
I mastered API integration optimization, user-centric UI design for writing tools, and subscription tier logic. Most importantly, I learned to prioritize actionable feedback over overwhelming users with too many suggestions.
What's next for this project
I plan to add citation formatting (APA/MLA/Chicago), expand audience subtypes for niche industries, and build lightweight integrations with Word/Google Docs. I also want to pilot a mobile web version for on-the-go writing checks.
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