Sambot is an innovative Chrome extension that employs machine learning to automatically generate predictions and insights. Ideal for businesses and professionals, it specializes in areas such as sales forecasts, stock trends, ad performances, and user behavior predictions. Users can initiate analyses by simply asking questions, receiving tailored data visualizations and recommendations that make understanding complex datasets easier. With its user-friendly interface, Sambot efficiently transforms intricate analysis into actionable insights.

Synna is a powerful platform that leverages AI and web scraping to automate data gathering and reporting tasks. By removing the need for manual data collection, Synna empowers companies to streamline their operations and optimize various processes. The platform's no-code interface makes it easily accessible for users of all technical backgrounds, ensuring that businesses can focus on analysis and strategic decision-making rather than tedious data retrieval tasks. Synna's AI-driven capabilities offer significant time savings and efficiency improvements, making it an invaluable tool for any organization looking to harness the power of data.

Temperstack is an AI-driven platform that enables users to efficiently manage, analyze, and visualize data through automation. It supports complex data transformations and analytics, empowering organizations to derive insights and drive strategic decisions. With an easy-to-use interface, users can seamlessly integrate dynamic data sources, execute predictive analytics, and automate routine tasks, making data-driven operations more effective and less time-consuming.

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.