Agent Shortlist

Enterprise platform

Vertex AI Agent Builder

Google Cloud's enterprise agent platform built on Gemini

3.5 / 5DeveloperUsage-based on Google Cloud: per-token Gemini model costs + Vertex AI infrastructure

Our verdict

Google's enterprise agent platform on Vertex AI. Best for Google Cloud teams wanting Gemini-native agents with BigQuery integration. Less useful elsewhere.

Best for

Engineering teams on Google Cloud who want to build agents using Gemini's long-context capabilities and integrate directly with BigQuery, Cloud Storage, and Google Workspace.

Not for

Teams not on Google Cloud — Vertex's value proposition is integration depth that doesn't transfer. Teams that want model flexibility — Vertex is Gemini-only.

Overview

Vertex AI Agent Builder is Google Cloud's enterprise agent platform. Built on Vertex AI (Google's ML platform) and integrated with the Gemini model family, it offers grounding via Google Search, knowledge ingestion from Google Workspace and BigQuery, and the same enterprise compliance story as the rest of Google Cloud. The differentiator is Gemini's long-context window — agents can hold 1M+ tokens of context, useful for codebase analysis or long-document workflows. Where Vertex falls short is model flexibility (Gemini-only) and the usual cross-cloud friction if your stack isn't already on Google Cloud. For teams already invested in Google Workspace and BigQuery, it's a natural extension. For everyone else, the integration advantage doesn't pay off.

What works

  • +Gemini's 1M+ token context window — the largest on the market
  • +Native integration with BigQuery, Cloud Storage, Google Workspace
  • +Grounding with Google Search built in (real-time web data)
  • +Google Cloud security, compliance, and IAM
  • +Free tier credits for new accounts make evaluation easy

What doesn't

  • Gemini-only — no Claude, GPT, or Llama support
  • Only makes sense if you're already on Google Cloud
  • Slower iteration than Anthropic or OpenAI direct
  • Documentation is dense and assumes Google Cloud familiarity
  • Enterprise contract overhead at scale

What operators use it for

01

BigQuery-Grounded Analytical Agents

Agents that answer business questions by querying BigQuery directly. Vertex's native BigQuery integration is the strongest of any agent platform.

02

Long-Context Document Analysis

Use Gemini's 1M+ token context window to analyse entire contracts, codebases, or document sets in a single pass. The longest context on the market.

03

Google Workspace Automation

Agents that read from Google Drive, Gmail, Calendar, and Sheets, then take actions back. Native integration is cleaner than third-party connectors.

04

Real-Time Web Grounding

Agents that need fresh web data — competitive intelligence, news monitoring, market research — get Google Search grounding built in.

05

Vertex AI Search Front-Ends

When you're already using Vertex AI Search to index enterprise content, Agent Builder is the natural conversational layer on top.

Pricing

Usage-based on Google Cloud: per-token Gemini model costs + Vertex AI infrastructure. Free tier credits available for new accounts.

Common questions about Vertex AI Agent Builder

What is Vertex AI Agent Builder?

Vertex AI Agent Builder is Google's hosted platform for building production AI agents on Google Cloud. Combines Gemini model access, ADK (Agent Development Kit), and managed orchestration into a single offering for enterprise customers.

How much does Vertex AI Agent Builder cost?

Usage-based on top of Gemini model costs. Google charges per agent action and per knowledge-base operation, with enterprise tiers including SLAs and dedicated support. Most enterprise deployments spend $500–$10,000/month.

Vertex AI Agent Builder vs ADK 2.0?

ADK (Agent Development Kit) is the open framework — code-first, runs anywhere. Vertex AI Agent Builder is the hosted offering on Google Cloud built around ADK. If you're already on GCP and want managed infrastructure, Agent Builder. If you want to run the same agent design anywhere, ADK directly.

Open dataset. This review is part of a structured dataset of every platform on the shortlist, published as platforms.json on GitHub under CC-BY-4.0.