
AgentPay-AI is a proof-of-concept platform that demonstrates how Generative AI services can be monetized using pay-per-use, token-based billing—similar to real-world AI APIs. Built with Streamlit and Google Gemini, the system simulates a USDC-style wallet that estimates token usage, deducts balance per request, and only executes AI tasks when sufficient funds are available. This project addresses a major gap in AI demos: cost transparency and usage accountability. AgentPay-AI showcases how AI-as-a-Service (AIaaS), agent marketplaces, and crypto-enabled AI platforms can implement realistic billing logic. Key Highlights: Token-based cost estimation Simulated USDC wallet per session Controlled AI execution based on balance Google Gemini / PaLM integration Simple, intuitive UI Designed as a hackathon and portfolio project for GenAI, SaaS, and Web3 applications.
24 Jan 2026

An AI-powered interactive web application built with Streamlit that predicts whether a candidate will get placed in a job (or admitted) based on academic performance and other features. The model simplifies decision-making for students, HR teams, and academic advisors by providing data-driven placement predictions. The user inputs academic and background features, including: SSC percentage HSC percentage Degree percentage MBA percentage Work experience Specialization Gender And more Inputs are one-hot encoded for categorical features. A Logistic Regression model (trained offline) is loaded using Pickle. The model outputs a binary prediction: “Placed” or “Not Placed”. The result is displayed on the Streamlit app in a clear, user-friendly format.
7 Dec 2025