
Gemini Enterprise Agent Platform is Google Cloud’s next-generation system for designing and managing advanced AI agents across the enterprise. Built as the successor to Vertex AI, it unifies model selection, development, and deployment into a single scalable environment. The platform supports a vast ecosystem of over 200 AI models, including Google’s latest Gemini innovations and popular third-party models. It offers flexible development tools like Agent Studio for visual workflows and the Agent Development Kit for deeper customization. Businesses can deploy agents that operate continuously, maintain long-term memory, and handle multi-step processes with high efficiency. Security and governance are central, with features such as agent identity verification, centralized registries, and controlled access through gateways. The platform also enables seamless integration with enterprise systems, allowing agents to interact with data, applications, and workflows securely. Advanced monitoring tools provide real-time insights into agent behavior and performance. Optimization features help refine agent logic and improve accuracy over time. By combining automation, intelligence, and governance, the platform helps organizations transition to autonomous, AI-driven operations. It ultimately supports faster innovation while maintaining enterprise-grade reliability and control.
Learn more

Anaconda is an AI-native development platform that gives teams a governed path from early experimentation to production AI deployment. The platform is built around trusted open-source packages, secure Python package management, controlled environments, and production-grade orchestration. Anaconda helps organizations avoid broken environments, dependency conflicts, security gaps, and deployment delays that can slow AI initiatives. Anaconda Core provides validated packages, automated security scanning, and intelligent dependency conflict resolution for Python and data science teams. Its platform capabilities support AI orchestration, trusted distribution, and enterprise workflows for building and scaling models. Anaconda is widely used across the AI, data science, Python, and enterprise developer communities. The company positions open source as a foundation for AI innovation and emphasizes Python as a core language for the next era of AI development. Anaconda also provides learning courses, certifications, reports, guides, professional services, documentation, and support resources. By combining package governance, environment management, open-source security, and AI development workflows, Anaconda helps teams build trusted AI systems on their own terms.
Learn more
Cegal Prizm
Cegal Prizm is a flexible solution crafted to facilitate the seamless integration of data from various geo-applications, data sources, and platforms within a Python ecosystem. Its modular structure enables users to merge geo-data sources for sophisticated analysis, visualization, data science workflows, and machine learning applications. This innovation empowers users to tackle challenges that were previously unmanageable with older systems. By incorporating contemporary Python technologies, you can enhance, speed up, and improve standard workflows while creating and securely sharing tailored code, services, and technologies with a user community for their use. Furthermore, it connects effortlessly with the E&P software platform Petrel, OSDU, and various third-party applications and domains, allowing for the access and retrieval of energy data. Data can be transferred smoothly, whether locally or across hybrid and cloud environments, into a unified Python setting to derive greater insights and added value. Additionally, Prizm enables the enhancement of datasets with supplementary application metadata, thereby providing more depth and context to your analytical processes. The ability to customize and share these enriched datasets among users fosters collaboration and innovation within the community.
Learn more
Polars
Polars offers a comprehensive Python API that reflects common data wrangling practices, providing a wide array of functionalities for manipulating DataFrames through an expression language that enables the creation of both efficient and clear code. Developed in Rust, Polars makes deliberate choices to ensure a robust DataFrame API that caters to the Rust ecosystem's needs. It serves not only as a library for DataFrames but also as a powerful backend query engine for your data models, allowing for versatility in data handling and analysis. This flexibility makes it a valuable tool for data scientists and engineers alike.
Learn more