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I used to think dashboards were just about making data look good.
The more I worked with data, the more I realized that's not the point.
A good dashboard should answer questions instantly.
• What's working?
• What needs attention?
• What should I do next?
If you still have to open five spreadsheets to find those answers, your data isn't really working for you.
That's the kind of problem I enjoy solving.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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A realtor or a business in need of python and LLM AI document processing? Here are some recaps of my previous internship I did.
Just completed some advanced level python and LLM from extern for a mortgage company.
Check out some of the project I've worked on
Engineered AI-powered document processing pipelines for 200+ page mortgage files using OCR technologies including Tesseract OCR, PaddleOCR, and PyMuPDF, enabling scalable document extraction and parsing.
Developed a Retrieval-Augmented Generation (RAG) system using LlamaIndex for intelligent document search, classification, and contextual retrieval workflows.
Improved retrieval accuracy and system performance through embedding optimization, chunking strategies, vector search tuning, and intelligent routing logic.
Delivered technical documentation, demo UI, and evaluation reports validating OCR accuracy, retrieval precision, and system readiness for production deployment.
github.com
GitHub - Kyl67899/Outamation_Externship_internship
Contribute to Kyl67899/Outamation_Externship_internship development by creating an account on GitHub.
The OCR plus RAG pipeline for 200-page mortgage files sounds like a serious test of retrieval quality. Which document type caused the toughest extraction or chunking issue?
Custom built CRM dashboard within Google Sheets that adjusts via automation to stay up-to-date based on incoming data.
Cleaned and automated a CRM system end-to-end — eliminating manual data-entry errors and building real-time dashboards that gave stakeholders instant visibility into operational trends.
