Google Vertex AI

Google Vertex AI, now evolved into Gemini Enterprise Agent Platform, is Google Cloud’s environment for developing, customizing, deploying, and managing machine learning, generative AI, and agentic applications. It combines model access, custom training, production AI services, and agent development within the Google Cloud ecosystem.

1. Model development: Model Garden provides access to Google, partner, and open models, while teams can train and deploy custom machine learning models using managed Google Cloud infrastructure. Model availability and deployment methods vary by model and region.
2. Agentic AI: the former Vertex AI Agent Builder capabilities now sit within Gemini Enterprise Agent Platform. Agent Runtime, previously called Agent Engine, provides managed production execution, while Sessions and Memory Bank maintain conversational and long-term context. The platform also includes agent evaluation, tracing, and observability capabilities.
3. Implementation checks: buyers should assess Google Cloud regions, IAM and networking, data location, available models, accelerator and compute requirements, quotas, security controls, and how existing Google Cloud services will connect to production AI workloads.
4. Commercial considerations: costs vary across model inference, custom training, deployed compute, agent runtime resources, sessions and memory services, and other platform components. Buyers running larger workloads should model expected usage and configure Google Cloud budgets, quotas, and capacity controls accordingly.

The platform is particularly relevant to organizations that want traditional machine learning, generative AI, and production agents managed within the same Google Cloud architecture.