Gartner 2025 Magic Quadrant for Data Science and ML Platforms

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AI is driving a radical transformation in how organizations operate, compete, and innovate. Working closely with customers, we’re delivering the innovations for a unified data and AI platform to meet the demands of the AI era, including data engineering and analysis, data science, MLOps, gen AI application and agent development tools, and a central layer of governance. 

Unified AI platform with best-in-class multimodal AI

Google Cloud offers a wide spectrum of AI capabilities, starting from the foundational hardware like Tensor Processing Units (TPUs) to AI agents, and the tools for building them. These capabilities are powered by our pioneering AI research and development, and our expertise in taking AI to production with large-scale applications such as YouTube, Maps, Search, Ads, Workspace, Photos, and more.

All of this research and experience fuels our Vertex AI platform, our unified AI platform for MLOps tooling, predictive and gen AI use cases, that sits at the heart of Google’s DSML offering. Vertex AI provides a comprehensive suite of tools covering the entire AI lifecycle, including data engineering and analysis tools, data science workbenches, MLOps capabilities for deploying and managing models, and specialized features for developing gen AI applications and agents. Moreover, our Self-Deploy capability enables our partners to not only build and host their models within Vertex AI for internal users, but also distribute and commercialize those models. Customer use of Vertex AI has grown 20x in the last year driven by Gemini, Imagen, and Veo models.

Vertex AI Model Garden offers a curated selection of over 200 enterprise-ready models from Google like Gemini, partners like Anthropic, and the open ecosystem. Model Garden helps customers access the highest performing foundation models suited for their business needs and easily customize them with their own data, deploy to applications with just one click, and scale with end-to-end MLOps built-in. 

Building on Google DeepMind research, we recently announced Gemini 2.5, our most intelligent AI model yet. Gemini 2.5 models are now thinking models, capable of reasoning (and showing its reasoning) before responding, resulting in dramatically improved performance. Transparent step-by-step reasoning is crucial for enterprise trust and compliance. We also launched Gemini 2.5 Flash, our cost-effective, low-latency workhorse model. Gemini 2.5 Flash will be generally available for all Vertex AI users in early June, with 2.5 Pro generally available soon after.

Vertex AI is now the only platform with generative media models across all modalities — video, image, speech, and music. At Google I/O, we announced several innovations in this portfolio, including the availability of Veo 3, Lyria 2, and Imagen 4 on Vertex AI. Veo 3 combines video and audio generation, taking content generation to a new level. The state-of-the-art model features improved quality when generating videos from text and image prompts. In addition, Veo 3 also generates videos with speech (dialogue and voice-overs) and audio (music and sound effects). Lyria 2, Google’s latest music generation model, features high-fidelity music across a range of styles. And Imagen 4, Google’s highest-quality image generation model, delivers outstanding text rendering and prompt adherence, higher overall image quality across all styles, and multilingual prompt support to help creators globally. Imagen 4 also supports multiple model variants to help customers optimize around quality, speed and cost.

All of this innovation resides on Vertex AI, so that AI projects can reach production and deliver business value while teams collaborate to improve models throughout the development lifecycle.

For instance, customers like Radisson Hotel Group have redefined personalized marketing with Google Cloud. Partnering with Accenture, the global hotel chain leveraged BigQuery, Vertex AI, Google Ads, and Google’s multimodal Gemini models to build a generative AI agent to help create locally relevant ad content and translate it into more than 30 languages — reducing content creation time from weeks to hours. This AI-driven approach has increased team productivity by 50%, boosted return on ad spend by 35%, and driven a 22% increase in ad-driven revenue.