AI agents designed to support research activities by gathering relevant information, analyzing data, summarizing findings, and even generating hypotheses. These agents assist in academic research, market analysis, scientific studies, and more, helping researchers to save time and focus on critical aspects of their work.

AI agents designed to assist developers in coding tasks. These agents can provide intelligent code suggestions, identify and fix bugs, automate repetitive coding tasks, and help developers follow best practices to write efficient and maintainable code.

AI agents that focus on processing and analyzing large datasets to extract valuable insights. These agents can perform statistical analysis, identify trends, visualize data, and generate reports, helping organizations make informed, data-driven decisions.

AI agents that use historical data and machine learning algorithms to predict future outcomes. These agents analyze patterns, trends, and correlations to provide insights for decision-making in areas such as marketing, finance, operations, and risk management.

Agents and frameworks provide the underlying structures and tools for developing and deploying AI models and applications. These frameworks enable developers to build, train, and optimize machine learning models more efficiently, offering pre-built components for tasks like data processing, model training, and deployment.