Pillar is a comprehensive AI agent framework designed to simplify the development and deployment of intelligent multi-step workflows. It features a modular architecture with planners for task decomposition, memory stores for context retention, and executors that perform actions via external APIs or custom code. Developers can define agent pipelines in YAML or JSON, integrate any LLM provider, and extend functionality through custom plugins. Pillar handles asynchronous execution and context management out of the box, reducing boilerplate code and accelerating time-to-market for AI-driven applications such as chatbots, data analysis assistants, and automated business processes.

SuperAnnotate provides an intuitive platform for annotating images and videos efficiently. With features like collaboration, customizable annotation tools, and integration with various ML frameworks, it enhances the data labeling process. Users can effortlessly manage large datasets while maintaining high accuracy, making it an ideal solution for data scientists and machine learning engineers seeking to accelerate their AI projects.