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Developed an AI-powered web application using Python, Streamlit, and NLP that combines a Research Paper Assistant and Resume Analyzer. The application enables users to upload research papers, extract key insights, ask questions, and analyze resumes by identifying missing skills, providing personalized recommendations, and suggesting improvements. It is designed to simplify research and help job seekers optimize their resumes using AI.
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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What does AI get wrong when you hand it a real brief?
I gave Kittl's agentic AI a brief we'd already shipped at Formeta, retail packaging for Ella by Ellaya Health, an at-home device for a common pelvic health condition, sold over the counter in Indian pharmacies. Plain language, no steering.
Pass one: four directions, three of them straight to the wellness reflex, lotus marks and sunrise gradients. All four were front faces attached to no box.
Pass two, with panel requirements and regulatory copy, came back with a real dieline. Glue flaps, directions for use, batch and expiry fields. Structurally a genuine leap.
It was also the wrong product. Invented a manufacturing licence number, added a CE mark to something sold only in India, moved the client to a different city.
On direction, Kittl is legitimately useful and I'd use it again. But healthcare packaging is a compliance problem wearing a design problem's clothes, and the model has no way to know it doesn't know that.
Vague brief gets you pretty. Precise brief gets you PLAUSIBLE. Plausible is the more dangerous one, because a founder without a designer might send it to print.
Last slide is the box we built.
Where do you let AI take the first swing, and where do you refuse?
It was super fun to experiment using Kittl with @Ansh Jamdagni 🫶
Completed my exam-proctoring SaaS — AI-powered exam creation, live proctoring, real-time analytics. Built with Next.js, LLM APIs, and computer-vision-based monitoring.
Supabase makes for a remarkably comprehensive edtech platform! Managing live video streams alongside real time behavioral analytics is no small feat. Exceptional engineering!
Q2 Product Insights | AI-powered research workspace.
A conceptual AI-powered research workspace designed to help users analyze product research, surface insights, and interact with their findings without leaving the document.
