This two-agent system automates HR onboarding and finance expense processing. The HR agent collects new recruit details name, start date, hiring manager, and emails then sends onboarding emails, generates a checklist, creates a Google Calendar meeting, and shares the link with all participants. The Finance agent reads a mock expense database containing date, amount, and submitter, analyzes each expense, updates the database with an approve decline escalate status, and sends notification emails to the manager. Together, they deliver fast, accurate, and end-to-end automation for HR and finance operations.
23 Nov 2025
In traditional finance, subscriptions are easy "set and forget" actions. In crypto, they are painfulโusers must remember to manually sign a transaction every single month for every service. If they forget, their service gets cut off. AgentPay solves this by combining AI natural language intent with smart contract automation on the Arc L1 blockchain. Users simply type a command like "Pay Spotify $10 every month" into our AI Command Bar. Our Natural Language Processing (NLP) engine decodes this intent, and our custom Solidity smart contracts (AgentPayScheduledPayments.sol) handle the recurring execution trustlessly on-chain. We chose Arc for its low fees and native USDC support, which makes micro-subscriptions finally viable in Web3. The project features a zero-friction demo mode that auto-signs transactions to instantly visualize payment flows for users.
8 Nov 2025
Climate Policy Maker is an AI-powered platform designed to assist governments, NGOs, researchers, and local communities in creating actionable climate policies. The system integrates LLM APIs with real-time weather and climate APIs to analyze environmental conditions, predict short-term climate changes, and highlight potential hazards such as floods, droughts, heatwaves, or storms. Users can select any region worldwide and instantly receive data-driven climate forecasts, interactive maps, and hazard visualizations. Based on this information, the LLM generates tailored policy recommendations that address local environmental challenges, ensuring decisions are rooted in science and aligned with sustainability goals. One of the key features is the ability to export policies in a professional PDF format, making them suitable for official use by policymakers, universities, or climate organizations. Beyond policy creation, the tool can also be used for urban planning, disaster preparedness, climate education, and sustainability reporting. By combining AI, data visualization, and environmental science, Climate Policy Maker bridges the gap between raw climate data and practical, region-specific strategies to combat climate change.
24 Aug 2025
