Develop tools for data integration, transformation, and cataloging, as well as Jupyter notebooks, SQL workbenches, and APIs. Add new capabilities for data integration, transformation, and visualization using LLMs. Optimize workflows for large-scale datasets and improve database support. Strengthen developer tools like Jupyter notebooks and SQL workbenches. Build next-generation features like cross-provider LLM APIs or integration with the latest Machine Learning models. Collaborate with research teams on innovative machine learning experiments. Enhance our collaborative Workspaces to organize and explore charts, dashboards, datasets and more. Create innovative interfaces that answer business questions and surface relevant insights using LLMs. Develop new chart types and optimize visualization performance. Enhance dash boarding capabilities to deliver fast and flexible experiences. Build tools to automate retraining, monitoring, and deployment of ML models. Enhance collaboration features for ML stakeholders. Optimize processing engines for scalability and latency. Expand capabilities to support new databases and cloud platforms. Develop customizable platforms for managing AI compliance and governance. Simplify policy enforcement and integration across disparate systems.