Lyria Integrations

Build, deploy, and scale machine learning (ML) models faster, with fully managed ML tools for any use case. Through Vertex AI Workbench, Vertex AI is natively integrated with BigQuery, Dataproc, and Spark. You can use BigQuery ML to create and execute machine learning models in BigQuery using standard SQL queries on existing business intelligence tools and spreadsheets, or you can export datasets from BigQuery directly into Vertex AI Workbench and run your models from there. Use Vertex Data Labeling to generate highly accurate labels for your data collection. Vertex AI Agent Builder enables developers to create and deploy enterprise-grade generative AI applications. It offers both no-code and code-first approaches, allowing users to build AI agents using natural language instructions or by leveraging frameworks like LangChain and LlamaIndex.

Google AI Studio is a unified development platform that helps teams explore, build, and deploy applications using Google’s most advanced AI models, including Gemini 3. It brings text, image, audio, and video models together in one interactive playground. With vibe coding, developers can use natural language to quickly turn ideas into working AI applications. The platform reduces friction by generating functional apps that are ready for deployment with minimal setup. Built-in integrations like Google Search enhance real-world use cases. Google AI Studio also centralizes API key management, usage monitoring, and billing. It offers a fast, intuitive path from prompt to production powered by vibe coding workflows.

Gemini is Google’s advanced AI assistant designed to help users think, create, learn, and complete tasks with a new level of intelligence. Powered by Google’s most capable models, including Gemini 3, it enables users to ask complex questions, generate content, analyze information, and explore ideas through natural conversation. Gemini can create images, videos, summaries, study plans, and first drafts while also providing feedback on uploaded files and written work. The platform is grounded in Google Search, allowing it to deliver accurate, up-to-date information and support deep follow-up questions. Gemini connects seamlessly with Google apps like Gmail, Docs, Calendar, Maps, YouTube, and Photos to help users complete tasks without switching tools. Features such as Gemini Live, Deep Research, and Gems enhance brainstorming, research, and personalized workflows. Available through flexible free and paid plans, Gemini supports everyday users, students, and professionals across devices.

Gemini Enterprise is a comprehensive AI platform built by Google Cloud designed to bring the full power of Google’s advanced AI models, agent-creation tools, and enterprise-grade data access into everyday workflows. The solution offers a unified chat interface that lets employees interact with internal documents, applications, data sources, and custom AI agents. At its core, Gemini Enterprise comprises six key components: the Gemini family of large multimodal models, an agent orchestration workbench (formerly Google Agentspace), pre-built starter agents, robust data-integration connectors to business systems, extensive security and governance controls, and a partner ecosystem for tailored integrations. It is engineered to scale across departments and enterprises, enabling users to build no-code or low-code agents that automate tasks, such as research synthesis, customer support response, code assist, contract analysis, and more, while operating within corporate compliance standards.

Music AI Sandbox is a set of experimental tools designed to spark new creative possibilities and help artists explore unique musical ideas. Developed in close collaboration with musicians, these tools are practical, useful, and can open doors to new forms of music creation. It includes features that allow users to generate fresh instrumental ideas by describing the desired sound, understanding genres, moods, vocal styles, and instruments. It generates musical continuations based on uploaded or generated audio clips, aiding in overcoming writer's block. It also enables users to transform the mood, genre, or style of an entire clip or make targeted modifications to specific parts, with intuitive controls for subtle tweaks or dramatic shifts. These tools help musicians discover new sounds, experiment with different genres, expand and enhance their musical libraries, or develop entirely new styles.

Gemini Robotics brings Gemini’s capacity for multimodal reasoning and world understanding into the physical world, allowing robots of any shape and size to perform a wide range of real-world tasks. Built on Gemini 2.0, it augments advanced vision-language-action models with the ability to reason about physical spaces, generalize to novel situations, including unseen objects, diverse instructions, and new environments, and understand and respond to everyday conversational commands while adapting to sudden changes in instructions or surroundings without further input. Its dexterity module enables complex tasks requiring fine motor skills and precise manipulation, such as folding origami, packing lunch boxes, or preparing salads, and it supports multiple embodiments, from bi-arm platforms like ALOHA 2 to humanoid robots such as Apptronik’s Apollo. It is optimized for local execution and has an SDK for seamless adaptation to new tasks and environments.

CodeMender is an AI-powered agent developed by DeepMind for automatically finding, diagnosing, and patching security vulnerabilities in software code. It combines advanced reasoning abilities (via Gemini Deep Think models) with program analysis tools, static analysis, dynamic analysis, differential testing, fuzzing, and SMT solvers, to identify root causes of flaws, generate high-quality fixes, and validate them to avoid regressions or functional breakage. CodeMender operates by proposing patches that adhere to style rules and structural correctness, and then uses critique and verification agents to check changes and self-correct if issues arise. It can also proactively rewrite existing code using safer APIs or data structures (for example, applying -fbounds-safety annotations to prevent buffer overflows). To date, CodeMender has upstreamed dozens of patches in large open source projects (including ones with millions of lines of code).

We’re beta launching SynthID, a tool for watermarking and identifying AI-generated images. SynthID is being released to a limited number of Vertex AI customers using Imagen, one of our latest text-to-image models that uses input text to create photorealistic images. With this tool, users can embed an imperceptible digital watermark into their AI-generated images and identify if Imagen was used for generating the image, or even part of the image. Being able to identify AI-generated content is critical to promoting trust in information. While not a silver bullet for addressing the problem of misinformation, SynthID is an early and promising technical solution to this pressing AI safety issue. This technology was developed by Google DeepMind and refined in partnership with Google Research. SynthID could be expanded for use across other AI models and we plan to integrate it into more products in the near future.