This project is an agentic investing app that profiles a user’s risk preferences, chooses a matching quantitative strategy from backtested research, expands that strategy into a real investable stock universe, ranks the stocks with technical indicators and sentiment, and builds a capital-weighted buy plan.
Team
Placement
ParticipantInjester is an AI-native engine that transforms "agent-hostile" websites into structured data interfaces. While the web was built for human attention, our…
Generating the first human preference datasets for robot policies in simulation with Nebius GPUs to understand which policies work best in an objective way…
RoboStore is a self-expanding robot agent platform that enables robots to autonomously detect their own capability gaps, search for hardware solutions in…
10 teams of LLM agents compete on a task. Each team has a randomly generated organizational genome — hierarchy, communication pattern, decision-making style…
Asha is a WhatsApp-native AI assistant that helps small home-based food businesses manage orders and remember customers — all through WhatsApp, with no apps…
robots that undestand the surroundings. location and mapping
