Custom Web Scraping & Business Data Automation Need data from websites without spending hours col...Custom Web Scraping & Business Data Automation Need data from websites without spending hours col...
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Need data from websites without spending hours collecting it manually?
I build custom web scraping and data automation systems that turn publicly accessible web data into clean, structured, and usable datasets.
What I Can Build?
Competitor & Product Monitoring
- Product prices
- Stock availability
- Product changes
- Promotions
- Competitor listings
- Price and catalog tracking
Business & Lead Data
- Business directories
- Company information
- Public business profiles
- Industry-specific datasets
- Location-based business data
Market & Research Data
- Product catalogs
- Real estate listings
- Job listings
- Market research datasets
- Public website content
- Custom datasets based on your requirements
Your Data, Your Workflow
Choose how you want your data delivered:
CSV • Excel • JSON • Google Sheets • API • Database
Need ongoing updates? I can build an automated pipeline that regularly collects new data, detects changes, and keeps your database or dashboard up to date.
From Website to Usable Data
Website
↓
Data Extraction
↓
Cleaning & Structuring
↓
Database / API / Spreadsheet
↓
Automated Updates
Built Around Your Requirements
Every website is different. Instead of using a one-size-fits-all scraper, I build the extraction workflow around the website and data you actually need.
You provide the target website and the information you want to collect. I'll analyze the available data structure, determine the appropriate extraction approach, and build the workflow accordingly.
Have a website you need data from?
Send me the URL and tell me what information you need. I'll review the requirements and determine the best approach.
Reading a document is easy. Understanding its meaning is the real challenge.
While building AI-powered medical document intelligence systems, I’ve been learning that extracting words is only one part of the problem.
Consider this sentence:
“Patient denies chest pain.”
A system might recognize the words correctly but still extract the wrong information if it ignores the word “denies.”
The same challenge appears in phrases like:
“No history of asthma”
“Mother had breast cancer”
“Rule out pneumonia”
“Aspirin discontinued”
Each sentence requires more than text recognition. It requires understanding context, negation, uncertainty, relationships, and whether information is current.
This is one of the challenges I’m exploring while building MDIS (Medical Document Intelligence System) at Cognate AI.
My focus is on developing systems that go beyond extracting information—toward structured outputs, validation, evidence traceability, and human review.
Because in healthcare AI, extracting the right words is not enough. The system must preserve what those words actually mean.
I’m continuing to learn, build, test, and improve this system one step at a time.
What do you think is the biggest challenge in making AI understand clinical language accurately?