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    AI and ML

    Documentation and resources for Google Cloud AI and ML products, covering platforms, pre-trained models, and tools for building smart applications.

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    Keep exploring with 20+ always-free products.

    Access 20+ free products for common use cases, including AI APIs, VMs, data warehouses, and more.

    Explore AI and ML in Google Cloud

    Read documentation and Cloud Architecture Center articles about AI and ML products, capabilities, and procedures.
    Support data engineering, data science, and ML engineering workflows on a unified platform, enabling you to train ML models and deploy AI solutions.
    Plan your approach with architecture center resources across a wide variety of AI & ML subjects.
    Plan for implementing ML, with a focus on custom-trained models based on your data and code.

    Training, blog articles, and more

    Go to training courses, blog articles, and other related resources.
    Study Vertex AI and Gemini in Google Cloud.
    Study designing, building, productionalizing, optimizing, operating, and maintaining ML systems.

    AI and ML products by use case

    Expand sections or use the filter to find products and guides for typical use cases.

    Explore documentation for building, deploying, and managing AI models and agents using Gemini Enterprise Agent Platform.

    A unified platform for building, deploying, and managing AI models and agents.
    An intranet search, AI assistant, and agentic platform.
    Discover, test, customize, and deploy select models and assets.

    Build and deploy complete agentic applications.

    Use ADK to streamline agent building.
    Secures and govern connectivity for all agentic interactions.
    Securely store, discover, and manage MCP servers, tools, and AI agents across your organization.
    A set of services that enables developers to deploy, manage, and scale AI agents in production.
    Design and test your agents.

    Ground your generative AI responses and provide accurate enterprise search.

    Google-quality search app on your own data.
    Organize siloed information into organizational knowledge.
    Ground agents by providing AI-powered, high-quality context for enterprise data assets.
    A data framework for developing context-augmented LLM applications.
    Perform vector similarity searches.

    Use collaborative, managed notebook environments.

    Use an integrated notebook-based production environment.
    A collaborative, managed notebook environment with the security and compliance capabilities of Google Cloud.
    Develop and deploy TensorFlow models.

    Train ML models from your data.

    Accelerate machine learning workloads using Tensor Processing Units.
    Use Docker containers pre-installed with key data science frameworks.
    Use virtual machine images optimized for data science and machine learning.
    Track and analyze experiments, model architectures, and training environments.
    Operationalize large-scale custom model training.
    Search for optimal neural architectures to improve accuracy, reduce latency, and optimize memory usage.
    Perform distributed computing and parallel processing for your ML workflow.

    Monitor, orchestrate, and serve your ML models.

    Run AI/ML workloads directly on scalable infrastructure.
    Orchestrate your complete AI/ML lifecycle with Kubernetes.
    Automate, monitor, and govern your ML systems using pipelines.
    Serve predictions from your trained models.
    Streamline ML feature management and online serving.
    Manage the complete lifecycle of your ML models.
    Provide model monitoring for feature skew and drift.
    Track, visualize, and compare ML experiments.

    Customer service, conversation, speech, and text

    Apply Google's advanced language and conversational AI capabilities.

    Empower human agents with continuous live support.
    Use advanced natural language understanding technologies.
    A collection of conversational AI tools and solutions.
    Handle complex conversations using virtual agents.
    Detect and visualize patterns in contact center data.
    Design standard conversational interfaces.
    Transform unstructured data from documents into structured data.
    Queue and route customer interactions across voice and digital channels.

    Speech-to-Text

    Integrate speech recognition technologies into developer applications.

    Text-to-Speech

    Convert text into natural-sounding speech.
    Dynamically translate text programmatically.

    Process and analyze your video streams and images at scale.

    Integrate vision detection features, including image labeling and face detection.
    Annotate videos or live streams with contextual information.
    Convert live video and package it for streaming.
    Convert video files and package them for optimized delivery.
    Process and analyze your video streams and images at scale.
    Dynamically insert ads into video-on-demand and live streams.

    Expand this section to see relevant products and documentation.

    A supercomputer architecture that employs systems-level codesign to boost efficiency and productivity across AI training, tuning, and serving.
    Use Google and Google Cloud services in your AI-powered applications with our remote Model Context Protocol servers.
    Ingest user event and catalog data and serve predictions or search results on your site.
    Detect suspicious, potential money laundering activity faster and more precisely with AI.
    Service that brings machine learning to the job search experience, returning high quality results to job seekers.
    Enable communication service providers to extract information to recommend actions to telecom customers.
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