Cheddar Flow offers real-time analytics on options order flow, helping traders make informed decisions. Its features include tracking dark pool orders, AI-powered alerts, and a customizable dashboard. The platform's cutting-edge technology makes it easier for users to spot unusual market activities and gain insights into potential trades. Cheddar Flow aims to empower both novice and experienced traders with actionable data to improve their trading strategies.

Maximo AI is an all-in-one solution that harnesses the power of artificial intelligence to enhance trading efficiency, improve content creation, and facilitate automation. It helps users make better trading decisions through advanced analytics and provides creative tools for engaging content development. This platform aims to simplify complex processes, offering a seamless experience for users across different domains, including finance and digital marketing.

Ultralgo is an advanced AI-powered trading platform that offers algorithmic trading solutions across various markets, including stocks, ETFs, options, and forex. Built by professional traders and powered by 15 technical indicators, Ultralgo provides users with reliable, automated, and high-yielding trading strategies. The platform is designed to help traders make informed decisions, optimize their trading performance, and achieve consistent results.

Multi-Agent-Seller provides a modular environment for simulating e-commerce negotiations using AI agents. It includes pre-built buyer and seller agents with customizable negotiation strategies, such as dynamic pricing, time-based concessions, and utility-based decision-making. Users can define custom protocols, message formats, and market conditions. The framework handles session management, offer tracking, and result logging with built-in visualization tools for analyzing agent interactions. It integrates easily with machine learning libraries for strategy development, enabling experimentation with reinforcement learning or rule-based agents. Its extensible architecture allows adding new agent types, negotiation rules, and visualization plugins. Multi-Agent-Seller is ideal for testing multi-agent algorithms, studying negotiation behaviors, and teaching concepts in AI and e-commerce domains.

ANAC-agents is a Python-based framework that centralizes multiple negotiation agent implementations for the Automated Negotiating Agents Competition (ANAC). Each agent within the repository embodies distinct strategies for utility modeling, proposal generation, concession tactics, and acceptance criteria, facilitating comparative studies and rapid prototyping. Users can define negotiation domains with custom issues and preference profiles, then simulate bilateral negotiations or tournament-style competitions across agents. The toolkit includes configuration scripts, evaluation metrics, and logging utilities to analyze negotiation dynamics. Researchers and developers can extend existing agents, test novel algorithms, or integrate external learning modules, accelerating innovation in automated bargaining and strategic decision-making under incomplete information.