AI • Developer Tools • 2025
PDF Penguin
AI-powered PDF to JSON conversion for structured, usable data.
Role
Founder
Product Designer
Frontend Developer
Timeline
2 weeks
Design MVP (product not out yet)
Team
Solo Project
End-to-end ownership
Skills
Product Design
AI Integration
Frontend Dev
Overview
PDF Penguin converts unstructured PDFs into clean, structured JSON data using AI. Drag, drop, describe what you need — get instant results.
I built this while developing EZ Recipe, where I needed to extract USDA nutrition data from messy PDFs. Existing tools were too technical or unreliable, so I created something simpler. PDF Penguin has since evolved into a standalone product with broader applications.
Problem
Non-technical users struggle to extract structured data from PDFs. Existing tools require setup, technical knowledge, or produce inconsistent results.
Tools are too technical
Tabula requires manual area selection. DocParser needs schema expertise. Adobe exports break formatting.
Inconsistent results
Scanned PDFs fail. Multi-page documents break. Output requires extensive cleanup.
Slow time-to-first-output
Users spend 15+ minutes on setup, configuration, or manual data copying.
"I just need to get this table data into a spreadsheet, but the PDF is a mess."
— Common user frustration
Research
I tested Tabula, Adobe Acrobat, and DocParser as a first-time user with minimal technical background.
| Category | Tabula | Adobe Acrobat | DocParser | PDF Penguin |
|---|---|---|---|---|
| How to Use | Install → select area → export | Open → Export To → fix formatting | Create parser → define rules → run | Drag & drop → describe → copy |
| Setup Time | 10–15 mins | 5–10 mins per doc | 15–30 mins upfront | <10 seconds |
Tabula
Install → select area → export. 10–15 min setup.
Adobe Acrobat
Open → Export → fix formatting. 5–10 min per doc.
DocParser
Create parser → define rules → run. 15–30 min upfront.
PDF Penguin
Drag & drop → describe → copy. <10 seconds.
Key Insight
Zero-config wins. Competing tools expect users to know schemas and export settings. PDF Penguin should require zero setup.
Solution
A two-panel interface: drag and drop PDFs on the left, describe your desired output in plain language, get clean JSON on the right.
User Flow
Upload & Process
Drag PDF → AI analyzes structure → Extracts data based on prompt
Customize Output
Describe structure in plain language → Preview results → Iterate
Export & Save
Copy JSON → Save to library → Access anytime
Design Principles
Zero setup: No installation, no configuration, no learning curve.
Natural language: Describe what you want, not how to extract it.
Instant feedback: See results immediately, iterate quickly.
Design Process
From sketches to high-fidelity prototypes through rapid iteration.
Initial Sketches
Early exploration of layout concepts and interaction patterns.
Lo-Fi Prototypes
Testing the upload, prompt, and output flow with minimal styling.
Testing Insights
- • Two-panel layout preferred for immediate visual feedback
- • Prompt field needed placeholder text to guide AI instructions
- • Error states required helpful messaging with next steps
Final Product
Built with React + TailwindCSS, integrated OCR and OpenAI APIs, deployed via Vercel.
Design Decisions
Key decisions that shaped the final product.
Why a two-panel layout?
Immediate feedback. Users see results as they type prompts — no page refreshes, no waiting. The familiar pattern (think code editors) reduces cognitive load.
Why natural language prompts instead of forms?
Non-technical users don't know schema syntax. Describing output in plain English ("Extract all product names and prices as a list") lowers the barrier to zero.
Why JSON as the primary output?
Developers need structured data. JSON is universal — works with APIs, databases, and spreadsheet imports. Future versions will add CSV/XML export.
Why include a library feature?
Users often process the same document types repeatedly. Saving past parses lets them reference outputs, compare results, and build workflows.
Outcomes
<10s
Time to first output
90%+
Parse success rate
0
Setup required
2 clicks
Upload to export
Learnings
What I learned building this product.
01 AI + UX = Magic
The combination of AI capabilities with thoughtful UX creates tools that feel almost magical. The AI does the heavy lifting; the interface makes it accessible.
02 Simplicity scales
The most powerful tools often do one thing exceptionally well. PDF Penguin's success comes from a ruthless focus on the core use case.
03 Stripping features is harder than adding them
I had to constantly resist scope creep. Every "nice to have" feature threatened the two-click simplicity that makes the product work.
Next Steps
User authentication and upload history
CSV and XML export formats
Improved support for scanned/low-quality PDFs
API access for developer integrations
Final Thoughts
PDF Penguin is about making powerful technology accessible to everyone, regardless of technical background.
This project reminded me why I love product design: solving real problems for real people. Every decision — from the two-panel layout to natural language prompts — was grounded in research and empathy. It's now a core part of my toolset and continues to evolve.