Discipline/data-automation
Data Automation & AI
We build web scrapers and data parsing pipelines that extract clean information without manual cleaning steps.
Our crawlers track 500 product sites daily, and our text parsers process resumes in 250ms.
Scraping & Data Processing
We write data pipelines and crawlers in Python using Pandas and Streamlit. We avoid fragile HTML selectors and instead use pattern-matching regex and layout-aware models to keep scrapers running when websites change.
NLP & Classification
- Custom text classification models
- spaCy and NLTK text processing
- Sentiment analysis and extraction
Data Pipe Standards
Deterministic Runs
We write idempotent jobs. Running the parser twice yields the exact same dataset without duplicate records.
Failure Throttling
We set up user-agent rotation and automatic retry delays so crawlers do not trigger rate limits or IP blocks.
Rapid Inference
We package machine learning models inside lightweight FastAPI servers to classify incoming text under 250ms.
Shipped Work
Competitive Intelligence Dashboard
We built a Python scraping system to crawl competitor prices and track market trends daily.
View project
NLP for Business Intelligence
We built a Python NLP service to parse candidate resumes and score matching skills in 250ms.
View project
Zabdoc
We built a Go utility on Cloudflare Workers to parse student grades and generate PDFs in 280ms.
View project
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