| Vertex AI | |
|---|---|
 | |
| Developer | Google Cloud |
| Initial release | May 18, 2021[1] |
| Operating system | Cloud-based |
| Platform | Google Cloud Platform |
| License | Proprietary |
| Website | cloud |
Vertex AI is a managed machine learning (ML) and artificial intelligence (AI) platform developed by Google Cloud. It provides a unified environment for building, training, deploying, and scaling ML models and generative AI applications.[2] The platform integrates tools for the full ML lifecycle, including data preparation, model training, evaluation, deployment, and monitoring, under a single API and user interface.[3]
Vertex AI was announced at Google I/O and released as a generally available product on May 18, 2021. At launch, Google described Vertex AI as unifying its AutoML offerings with its prior Cloud AI Platform capabilities, and as adding operational features intended to help teams move models from experimentation into production use.[1][4]
History
Google Cloud announced the general availability of Vertex AI on May 18, 2021, at the Google I/O developer conference.[5] The platform was designed to consolidate Google Cloud's previously separate ML offerings, including AutoML and the legacy AI Platform, into a single system.[6] At launch, Google claimed that Vertex AI required roughly 80% fewer lines of code to train a model compared to competing platforms.[7]
In June 2023, Google made generative AI support in Vertex AI generally available, giving developers access to foundation models including PaLM 2, Imagen, and Codey through the platform's Model Garden and the newly launched Generative AI Studio.[8] At the time of this launch, Model Garden included over 60 models from Google and its partners.[9]
In August 2023, at the Google Cloud Next conference, Google announced further updates to Vertex AI, including the addition of third-party models such as Claude 2 from Anthropic and Llama 2 from Meta to the Model Garden, as well as new tools called Vertex AI Extensions for connecting models to APIs for real-time data retrieval.[10] At the same event, Vertex AI Search and Conversation were made generally available, providing enterprise search and chatbot capabilities powered by foundation models.[10]
In April 2024, at Google Cloud Next, the company introduced Vertex AI Agent Builder, a no-code tool for creating AI-powered conversational agents built on top of Gemini large language models.[11] This brought together the existing Vertex AI Search and Conversation products with new developer tools for building generative AI experiences.[12]
Features
Model training
Vertex AI supports both AutoML, which enables code-free model training on tabular, image, text, or video data, and custom training, which gives users full control over the ML framework, training code, and hyperparameter tuning.[2] The platform provides serverless training as well as dedicated training clusters with GPU and TPU accelerators.[2] Vertex AI Vizier handles automatic hyperparameter tuning, and Vertex AI Experiments allows comparison and tracking of training runs.[3]
Model Garden
The Vertex AI Model Garden is a curated catalog of over 200 enterprise-ready models, including Google's own foundation models (such as Gemini, Imagen, and Veo), third-party models (such as Anthropic's Claude and Mistral AI models), and popular open-source models (such as Llama and Gemma).[2] Models are accessible as fully managed model-as-a-service APIs.[2]
Pipelines (workflow orchestration)
Vertex AI Pipelines provides managed orchestration of ML workflows and supports pipelines built with the Kubeflow Pipelines SDK, among other options described in Google Cloud documentation.[13]
Vertex AI Studio
Vertex AI Studio provides tools for prompt design, testing, and model management, allowing developers to prototype and build generative AI applications using natural language, code, images, or video.[14]
Agent Builder and Agent Engine
Vertex AI Agent Builder is a suite of products for building, deploying, and governing AI agents in production environments. It supports development with the open-source Agent Development Kit (ADK) and other frameworks.[15] Vertex AI Agent Engine provides the underlying infrastructure for deploying and scaling agents, with support for enterprise security features including HIPAA compliance, customer-managed encryption keys (CMEK), and VPC Service Controls.[16]
Generative AI tooling and model access
Google markets Vertex AI as providing access to Google foundation models (including the Gemini family) and developer tools such as Vertex AI Studio, along with a model catalog that includes Google and selected open source models (marketed as "Model Garden").[17]
Google has also offered products within Vertex AI aimed at building generative search and conversational applications, including offerings named "Vertex AI Search" and "Vertex AI Conversation" as reported in 2023 coverage of platform updates.[18]
MLOps tools
The platform includes a range of MLOps capabilities:
- Vertex AI Pipelines for orchestrating and automating ML workflows as reusable pipelines.[2]
- Vertex AI Feature Store for serving, sharing, and reusing ML features across projects.[3]
- Vertex AI Model Registry for storing, versioning, and managing trained models.[2]
- Vertex AI Model Monitoring for detecting training-serving skew and inference drift in deployed models.[2]
- Vertex Explainable AI for interpreting model predictions.[2]
- Vertex AI Workbench for managed JupyterLab notebook environments integrated with Google Cloud Storage and BigQuery.[2]
Industry recognition
Google was named a Leader for the fifth consecutive year in the 2024 Gartner Magic Quadrant for Cloud AI Developer Services, a recognition that encompasses Vertex AI and its related offerings.[19] Google was also recognized as a Leader in the 2024 Gartner Magic Quadrant for Data Science and Machine Learning Platforms[20] and was named a Leader in the Forrester Wave for AI/ML Platforms, Q3 2024.[14]
In October 2025, Google was also named a Leader in the 2025 IDC MarketScape for Worldwide GenAI Life-Cycle Foundation Model Software.[21]
Pricing
Vertex AI uses a pay-as-you-go pricing model, with costs determined by the specific services consumed, including model training, prediction serving, and data storage.[22] For generative AI tasks, pricing is based on a per-token model, with rates varying depending on the specific model used and whether tokens are input or output.[22] Google offers a free tier for new users, which includes limited custom training hours and online prediction usage, along with an introductory US$300 in Google Cloud credits valid for 90 days.[23]
Adoption
In the year following its 2021 launch, Google reported that usage of Vertex AI and BigQuery had driven 2.5 times more machine learning predictions compared to the prior year, and that active customers of Vertex AI Workbench had grown 25-fold over a six-month period.[24] Early enterprise adopters included Ford, Wayfair, and Seagate, among others.[24] Wayfair reported that it was able to run large model training jobs 5 to 10 times faster using the platform.[24]
See also
References
- ^ a b Wiley, Craig (May 18, 2021). "Google Cloud unveils Vertex AI, one platform, every ML tool you need". Google Cloud Blog. Google Cloud. Retrieved 20 February 2026.
- ^ a b c d e f g h i j "Overview of Vertex AI". Google Cloud Documentation. Retrieved February 20, 2026.
- ^ a b c "Google Cloud launches Vertex AI, unified platform for MLOps". Google Cloud Blog. May 18, 2021. Retrieved February 20, 2026.
- ^ Krill, Paul (May 18, 2021). "Google Vertex AI unifies cloud machine learning toolkit". InfoWorld. Retrieved 20 February 2026.
- ^ Miller, Ron (May 18, 2021). "Google Cloud launches Vertex AI, a new managed machine learning platform". TechCrunch. Retrieved February 20, 2026.
- ^ "What is Vertex AI? Unpacking Google's ML Platform". DigitalOcean. Retrieved February 20, 2026.
- ^ "Google launches Vertex AI, a fully managed cloud AI service". VentureBeat. May 18, 2021. Retrieved February 20, 2026.
- ^ Miller, Ron (June 7, 2023). "Google's generative AI support in Vertex AI is now generally available". TechCrunch. Retrieved February 20, 2026.
- ^ "Generative AI support on Vertex AI generally available". Google Cloud Blog. June 7, 2023. Retrieved February 20, 2026.
- ^ a b Kerner, Sean Michael (August 29, 2023). "Google updates Vertex AI with new models, expands reach". TechTarget. Retrieved February 20, 2026.
- ^ Miller, Ron (April 9, 2024). "With Vertex AI Agent Builder, Google Cloud aims to simplify agent creation". TechCrunch. Retrieved February 20, 2026.
- ^ "Build generative AI experiences with Vertex AI Agent Builder". Google Cloud Blog. April 9, 2024. Retrieved February 20, 2026.
- ^ "Build a pipeline". Google Cloud Documentation. Google Cloud. Retrieved 20 February 2026.
- ^ a b "Vertex AI Platform". Google Cloud. Retrieved February 20, 2026.
- ^ "Vertex AI Agent Builder overview". Google Cloud Documentation. Retrieved February 20, 2026.
- ^ "Vertex AI Agent Engine overview". Google Cloud Documentation. Retrieved February 20, 2026.
- ^ "Vertex AI Platform". Google Cloud. Google Cloud. Retrieved 20 February 2026.
- ^ "Google upgrades Vertex AI to keep pace with the generative AI boom". TechCrunch. August 29, 2023. Retrieved 20 February 2026.
- ^ "Google is a Leader in the 2024 Gartner Magic Quadrant for Cloud AI Developer Services". Google Cloud Blog. May 1, 2024. Retrieved February 20, 2026.
- ^ "Google is a Leader in the 2024 Gartner Magic Quadrant for Data Science and Machine Learning Platforms". Google Cloud Blog. June 20, 2024. Retrieved February 20, 2026.
- ^ "Google named a Leader in the 2025 IDC MarketScape". Google Cloud Blog. October 20, 2025. Retrieved February 20, 2026.
- ^ a b "Vertex AI Pricing". Google Cloud. Retrieved February 20, 2026.
- ^ "Vertex AI Pricing Review". Lindy. January 8, 2026. Retrieved February 20, 2026.
- ^ a b c "How Businesses Use Google Cloud Vertex AI". Google Cloud Blog. June 9, 2022. Retrieved February 20, 2026.
