SeeAct is designed to empower vision-language agents with a two-stage pipeline: a planning module powered by large language models generates subgoals based on observed scenes, and an execution module translates subgoals into environment-specific actions. A perception backbone extracts object and scene features from images or simulations. The modular architecture allows easy replacement of planners or perception networks and supports evaluation on AI2-THOR, Habitat, and custom environments. SeeAct accelerates research on interactive embodied AI by providing end-to-end task decomposition, grounding, and execution.

TextQL is a powerful AI tool that allows users to extract data and insights from various databases using simple and intuitive natural language queries. It converts complex queries into language that users can easily understand and utilize, thus streamlining the process of data analysis and reporting. This makes data-driven decision-making more accessible for users with varying levels of technical expertise.

The Attic AI leverages advanced technology to revolutionize how enterprises handle and manage knowledge. By converting unstructured data into an intelligent, secure, and searchable database, it empowers organizations to streamline information access, increase operational efficiency, and support the modern distributed work environment. The platform is built on proprietary models, providing a safe and secure solution that ensures data privacy and can be deployed anywhere, making it a versatile tool for businesses of all sizes.

Heimdall is an innovative machine learning platform designed to help businesses build, deploy, and monitor robust machine learning models. The platform eliminates the barriers to entry in data science by providing scalable solutions, model explainability, and an easy-to-use interface. Whether you are dealing with text, images, or location data, Heimdall helps convert raw data into actionable insights, enabling organizations to make data-driven decisions and stay competitive.