Google is a Leader in the 2024 Gartner® Magic Quadrant™ for Cloud AI Developer Services

For the fifth consecutive year, Gartner® has named Google as a Leader in the Magic Quadrant™ for Cloud AI Developer Services (CAIDS). We believe this is a testament to our history of offering innovative AI products and delivering continuous improvement for our customers.

2024 Gartner CAIDS MQ graphic

Download the complimentary 2024 Gartner Magic Quadrant™ for Cloud AI Developer Services report.

Google has two decades of experience building and running advanced AI workloads at scale. We funneled this experience into Vertex AI, which launched nearly four years ago with the goal of providing the best AI/ML platform for accelerating AI workloads — one platform, every ML tool an organization needs. Over the past year, we’ve expanded our offering for generative AI, bringing developers the widest variety of foundation models from any hyperscale provider, robust infrastructure options, and tooling for model development and MLOps.

The rise of generative AI has brought enormous potential for organizations to increase revenue and reduce costs. From automating business processes to enhancing web experiences and improving customer service, the applications of generative AI are endless. But to capitalize on this potential, developers need to overcome a range of challenges, including balancing the rapid experimentation and iteration of AI models, apps, and agents with costs, governance, and performance at scale.

Our aim is to help our customers manage these obstacles and accelerate AI adoption, whether they are just getting started with a couple use cases or working to operationalize AI across their organization.

Recently, at Google Cloud Next 2024 we announced new capabilities that further empower developers:

Giving customers the best selection of enterprise-ready models

Vertex AI provides customers with the widest selection of pre-trained and foundation models among hyperscale providers, enabling rapid deployment across vision, language, conversation, and structured data.

Model Garden provides a curated selection of enterprise-ready models, including first-party, open, and partner models. This set of 130+ models offers leading options across an array of categories; from large frontier models to small models that can run on device, helping customers access the foundation models that are best-suited for their business needs.

  • Google models include Gemini, Imagen for text-to-image, Chirp for speech-to-text and more
  • Open and Partner models such as Google’s Gemma, Meta’s Llama 3, TII’s Falcon, BERT, T-5 FLAN, ViT, EfficientNet, and Anthropic’s Claude 3

We make these models easily accessible for developers via easy-to-use SDKs and APIs in the most common languages.

For customers looking for even more variety, we offer an integration with Hugging Face that enables one-click model deployment from Hugging Face to Vertex AI.

Build, tune, deploy, and manage foundation models

Vertex AI Model Builder helps developers and data scientists access, customize, and monitor foundation models for their business needs and deploy them to production. This includes a robust set of tuning capabilities, making it easy for developers of all skill levels to customize models with:

  • Prompt design, which lets developers give the model instructions
  • Supervised tuning, including adapter-based and Low-Rank Adaptation (LoRA), which allows developers to customize the model in an efficient, lower-cost way
  • Reinforcement Learning from Human Feedback (RLHF), which helps organizations align model outputs with human values
  • Distillation, which lets teams transfer knowledge from a larger model to a smaller model

We’ve also expanded Vertex AI’s MLOps tools to meet the needs of both predictive and generative AI, with recent updates including:

  • Prompt assistance and management tools to version prompts and track lineage, share notes, run side-by-side comparisons, and even use AI assisted prompting
  • Rapid evaluation (in preview), which allows developers to quickly evaluate model performance in seconds based on a small data set
  • Evaluation with Automatic side-by-side, which is now GA and uses one large language model to evaluate two other models, providing explanations and certainty scores to help evaluate models at scale.

For those interested in building their own predictive models from scratch, Vertex AI makes model building easy with not only tools for training and serving models, but also AutoML to supercharge the model building journey.

Easily build and deploy gen AI agents

Vertex AI Agent Builder lets developers easily build and deploy enterprise-ready gen AI experiences via a range of tools for different developer needs and levels of expertise — from a no-code console for building AI agents using natural language, to open-source frameworks like LangChain on Vertex AI.

Additionally, Vertex AI Agent Builder streamlines the process of grounding generative AI outputs in enterprise data. It offers not only Vertex AI Search as an out-of-the-box grounding system, but also RAG (or retrieval augmented generation) component APIs for document layout processing, ranking, retrieval, and performing checks on grounding outputs. Developers can also use Vertex AI Vector Search to build embeddings-based agents and applications, increasing the accuracy and usefulness of model responses.

And now, customers also have the option of grounding model outputs in Google Search, combining the power of Google’s latest foundation models with access to fresh, high-quality information that can significantly improve completeness and accuracy of responses. Google is the only cloud provider to offer customers out-of-the-box grounding capabilities on both their own data and Google Search results.

Leading AI companies are building on Vertex AI

Customers choose Vertex AI because Google Cloud helps provide the necessary trust for organizations to confidently deploy their services. Built-in mechanisms such as data governance, security, IP indemnity, and responsible AI best practices help ensure that organizations can go into production with peace of mind.

Vertex AI also provides a comprehensive set of capabilities that help accelerate time-to-value across use cases. Domain-specific models such as MedLM, our family of foundation models built on Med-PaLM 2, and Healthcare Data Engine supercharge healthcare industry use cases. Likewise, Sec-PaLM, a specialized version of PaLM 2 trained on cybersecurity data, and Anti Money Laundering AI help security and financial services use cases.

Altogether, Vertex AI helps organizations build transformative generative AI experiences with confidence and speed. For example, United Wholesale Mortgage is using Gemini to enrich the underwriting process and automate the mortgage application process. TBS, one of the main commercial broadcasters in Japan, is using Gemini 1.5 Pro to automate metadata tagging on their large media archives, significantly improving efficiency for finding materials in production process.

With Vertex AI Agent Builder, ADT is building an agent to help its millions of customers select and set up their home security systems; IHG Hotels & Resorts is building a generative AI-powered chatbot to help guests easily plan their next vacation directly in the IHG One Rewards mobile app, and NewsCorp is using Vertex AI to help search data across 30,000 global sources and 2.5 billion news articles updated daily.

Other customers are building agents to boost internal efficiency. For example, researchers at Mayo Clinic have given thousands of its scientific researchers access to 50 petabytes worth of clinical data through Vertex AI search, accelerating information retrieval across multiple languages. Vodafone uses Vertex AI to search and understand specific commercial terms and conditions across more than 10,000 contracts with more than 800 communications operators. We’re thrilled to see this momentum and look forward to continued customer innovation in the months to come.

What’s next

Google Cloud is committed to helping organizations build and deploy AI. We are investing heavily in bringing new generative AI offerings for developers. To download the full report, click here, and for more information on our new generative AI offerings see here.

Gartner, Magic Quadrant for Cloud AI Developer Services, Jim Scheibmeir, Arun Batchu, Mike Fang – April 29, 2024. GARTNER is a registered trademark and service mark of Gartner and Magic Quadrant is a registered trademark of Gartner Inc, and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved. This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Google. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.