---
title: ResearchLens
emoji: 🔎
colorFrom: blue
colorTo: indigo
sdk: static
app_file: index.html
pinned: false
license: mit
short_description: Multilingual document intelligence in the browser
---

# ResearchLens

A privacy-conscious, browser-first multilingual NLP application for academic, policy and business documents.

This Static Space analyzes English, Spanish and Portuguese text without server-side compute or a generative API. It provides document metrics, an extractive summary, lexical signals and multilingual topic indicators. PDF extraction is performed in the browser with PDF.js.

## Why a Static Space?

The portfolio uses scarce compute only where machine-learning inference materially adds value. ResearchLens relies on transparent analytical NLP, so moving it to a Static Space makes the project faster to share, cheaper to maintain and more privacy-friendly.

## Capabilities

- paste text or upload PDF/TXT/Markdown
- English, Spanish and Portuguese language detection
- word, sentence and paragraph metrics
- reading-time estimate
- lexical diversity
- extractive summarization
- unigram and bigram lexical signals
- multilingual topic scoring
- fully client-side analysis

## Technical design

- Vanilla JavaScript
- deterministic NLP heuristics
- PDF.js for browser-side PDF text extraction
- no backend
- no API keys
- no external generative AI service

## Limitations

- Scanned/image-only PDFs require OCR and may not extract text.
- Language detection is heuristic.
- Extractive summaries preserve source sentences but can miss nuance.
- Topic signals are based on a curated lexicon rather than a learned classifier.
- Results are analytical signals, not factual verification.

## License

MIT for project code. PDF.js is loaded from its public distribution and remains subject to its own license.