Galileo 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.

OpenAI’s mission is to ensure that artificial general intelligence (AGI)—by which we mean highly autonomous systems that outperform humans at most economically valuable work—benefits all of humanity. We will attempt to directly build safe and beneficial AGI, but will also consider our mission fulfilled if our work aids others to achieve this outcome. Apply our API to any language task — semantic search, summarization, sentiment analysis, content generation, translation, and more — with only a few examples or by specifying your task in English. One simple integration gives you access to our constantly-improving AI technology. Explore how you integrate with the API with these sample completions.

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 Advanced is a cutting-edge AI model designed for unparalleled performance in natural language understanding, generation, and problem-solving across diverse domains. Featuring a revolutionary neural architecture, it delivers exceptional accuracy, nuanced contextual comprehension, and deep reasoning capabilities. Gemini Advanced is engineered to handle complex, multifaceted tasks, from creating detailed technical content and writing code to conducting in-depth data analysis and providing strategic insights. Its adaptability and scalability make it a powerful solution for both individual users and enterprise-level applications. Gemini Advanced sets a new standard for intelligence, innovation, and reliability in AI-powered solutions. You'll also get access to Gemini in Gmail, Docs, and more, 2 TB storage, and other benefits from Google One. Gemini Advanced also offers access to Gemini with Deep Research. You can conduct in-depth and real-time research on almost any subject.

Gemini 2.0 is an advanced AI-powered model developed by Google, designed to offer groundbreaking capabilities in natural language understanding, reasoning, and multimodal interactions. Building on the success of its predecessor, Gemini 2.0 integrates large language processing with enhanced problem-solving and decision-making abilities, enabling it to interpret and generate human-like responses with greater accuracy and nuance. Unlike traditional AI models, Gemini 2.0 is trained to handle multiple data types simultaneously, including text, images, and code, making it a versatile tool for research, business, education, and creative industries. Its core improvements include better contextual understanding, reduced bias, and a more efficient architecture that ensures faster, more reliable outputs. Gemini 2.0 is positioned as a major step forward in the evolution of AI, pushing the boundaries of human-computer interaction.

LangChain is a powerful, composable framework designed for building, running, and managing applications powered by large language models (LLMs). It offers an array of tools for creating context-aware, reasoning applications, allowing businesses to leverage their own data and APIs to enhance functionality. LangChain’s suite includes LangGraph for orchestrating agent-driven workflows, and LangSmith for agent observability and performance management. Whether you're building prototypes or scaling full applications, LangChain offers the flexibility and tools needed to optimize the LLM lifecycle, with seamless integrations and fault-tolerant scalability.

Gemini is natively multimodal, which gives you the potential to transform any type of input into any type of output. We've built Gemini responsibly from the start, incorporating safeguards and working together with partners to make it safer and more inclusive. Integrate Gemini models into your applications with Google AI Studio and Google Cloud Vertex AI.

The Gemini 2.0 Flash AI model represents the next generation of high-speed, intelligent computing, designed to set new benchmarks in real-time language processing and decision-making. Building on the robust foundation of its predecessor, it incorporates enhanced neural architecture and breakthrough advancements in optimization, enabling even faster and more accurate responses. Gemini 2.0 Flash is designed for applications requiring instantaneous processing and adaptability, such as live virtual assistants, automated trading systems, and real-time analytics. Its lightweight, efficient design ensures seamless deployment across cloud, edge, and hybrid environments, while its improved contextual understanding and multitasking capabilities make it a versatile tool for tackling complex, dynamic workflows with precision and speed.

Gemini Nano from Google is a lightweight, energy-efficient AI model designed for high performance in compact, resource-constrained environments. Tailored for edge computing and mobile applications, Gemini Nano combines Google's advanced AI architecture with cutting-edge optimization techniques to deliver seamless performance without compromising speed or accuracy. Despite its compact size, it excels in tasks like voice recognition, natural language processing, real-time translation, and personalized recommendations. With a focus on privacy and efficiency, Gemini Nano processes data locally, minimizing reliance on cloud infrastructure while maintaining robust security. Its adaptability and low power consumption make it an ideal choice for smart devices, IoT ecosystems, and on-the-go AI solutions.

The Gemini 1.5 Pro AI model is a state-of-the-art language model designed to deliver highly accurate, context-aware, and human-like responses across a variety of applications. Built with cutting-edge neural architecture, it excels in natural language understanding, generation, and reasoning tasks. The model is fine-tuned for versatility, supporting tasks like content creation, code generation, data analysis, and complex problem-solving. Its advanced algorithms ensure nuanced comprehension, enabling it to adapt to different domains and conversational styles seamlessly. With a focus on scalability and efficiency, the Gemini 1.5 Pro is optimized for both small-scale implementations and enterprise-level integrations, making it a powerful tool for enhancing productivity and innovation.

The Gemini 1.5 Flash AI model is an advanced, high-speed language model engineered for lightning-fast processing and real-time responsiveness. Designed to excel in dynamic and time-sensitive applications, it combines streamlined neural architecture with cutting-edge optimization techniques to deliver exceptional performance without compromising on accuracy. Gemini 1.5 Flash is tailored for scenarios requiring rapid data processing, instant decision-making, and seamless multitasking, making it ideal for chatbots, customer support systems, and interactive applications. Its lightweight yet powerful design ensures it can be deployed efficiently across a range of platforms, from cloud-based environments to edge devices, enabling businesses to scale their operations with unmatched agility.

Amazon SageMaker is an advanced machine learning service that provides an integrated environment for building, training, and deploying machine learning (ML) models. It combines tools for model development, data processing, and AI capabilities in a unified studio, enabling users to collaborate and work faster. SageMaker supports various data sources, such as Amazon S3 data lakes and Amazon Redshift data warehouses, while ensuring enterprise security and governance through its built-in features. The service also offers tools for generative AI applications, making it easier for users to customize and scale AI use cases. SageMaker’s architecture simplifies the AI lifecycle, from data discovery to model deployment, providing a seamless experience for developers.

Apply advanced coding and language models to a variety of use cases. Leverage large-scale, generative AI models with deep understandings of language and code to enable new reasoning and comprehension capabilities for building cutting-edge applications. Apply these coding and language models to a variety of use cases, such as writing assistance, code generation, and reasoning over data. Detect and mitigate harmful use with built-in responsible AI and access enterprise-grade Azure security. Gain access to generative models that have been pretrained with trillions of words. Apply them to new scenarios including language, code, reasoning, inferencing, and comprehension. Customize generative models with labeled data for your specific scenario using a simple REST API. Fine-tune your model's hyperparameters to increase accuracy of outputs. Use the few-shot learning capability to provide the API with examples and achieve more relevant results.

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.

Amazon Bedrock is a fully managed service that simplifies building and scaling generative AI applications by providing access to a variety of high-performing foundation models (FMs) from leading AI companies such as AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon itself. Through a single API, developers can experiment with these models, customize them using techniques like fine-tuning and Retrieval Augmented Generation (RAG), and create agents that interact with enterprise systems and data sources. As a serverless platform, Amazon Bedrock eliminates the need for infrastructure management, allowing seamless integration of generative AI capabilities into applications with a focus on security, privacy, and responsible AI practices.

PaLM 2 is our next generation large language model that builds on Google’s legacy of breakthrough research in machine learning and responsible AI. It excels at advanced reasoning tasks, including code and math, classification and question answering, translation and multilingual proficiency, and natural language generation better than our previous state-of-the-art LLMs, including PaLM. It can accomplish these tasks because of the way it was built – bringing together compute-optimal scaling, an improved dataset mixture, and model architecture improvements. PaLM 2 is grounded in Google’s approach to building and deploying AI responsibly. It was evaluated rigorously for its potential harms and biases, capabilities and downstream uses in research and in-product applications. It’s being used in other state-of-the-art models, like Med-PaLM 2 and Sec-PaLM, and is powering generative AI features and tools at Google, like Bard and the PaLM API.