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  7. Google Cloud AutoML

Google Cloud AutoML logo

Google Cloud AutoML

Approaching Agent-Ready
Agent-Ready SaaS Index · cloud.google.com · scored 2026-05-06 · rubric v1.1
Score 67 / 100
Machine Learning
Self-serve checkout
Public API

Google Cloud AutoML publishes a pricing page with 3 discoverable plan tier(s). No per-unit price was found on the page; an agent has no direct way to estimate the cost of a single task. Self-serve signup exists alongside a sales-led / custom tier. Public API documentation is reachable without an auth wall.

See Google Cloud AutoML pricing summaryLive pricing page
Pricing
Google Cloud AutoML pricing
As of 2026-05-09 · cloud.google.com/automl-tables/pricing
Pricing — verifying
We’re still verifying Google Cloud AutoML’s pricing

No pricing figures or tier details were present in the provided body text, so the record is marked as unverified with minimal inferred information.

Source of truth: cloud.google.com/automl-tables/pricing

Score breakdown · rubric v1.1
How Google Cloud AutoML scores on the agent-ready dimensions

Public pricing

15 / 15

Usage-based / metered

0 / 25

Self-serve checkout

15 / 15

Public API

15 / 15

Low / no minimum

0 / 10

Unauth automated payment

3 / 10

Bonus (machine-readable pricing)On top of /100 base

0 / 5

Total
67 / 100
Agent purchase simulation
Six-step check: can an agent actually buy from Google Cloud AutoML?
✓

Discover price

✓

Select a plan

✗

Pay per task

✗

Avoid a sales call

◐

API docs without auth

✗

Estimate cost upfront

Analysis
Pros and cons for AI agents
Observational summary written by xpay from the signals captured on 2026-05-06. Not a review of the product — only of its current pricing posture for agent buyers.
✓ For an AI agent
  • Pricing is publicly visible on an indexable page — agents can read tiers without scraping past auth.
◐ Opportunities for the provider
  • No per-unit price was advertised, so an agent has no way to estimate the cost of a single task.
  • All advertised tiers route to a sales contact form; an agent cannot complete a purchase autonomously.
  • API documentation is gated or absent; an agent cannot inspect the integration surface without authentication.
  • PPU requires account creation and an issued API key; a fully unauthenticated agent purchase is not yet supported.
  • No /.well-known/ai-pricing.json or equivalent machine-readable pricing manifest is published — agents must rely on HTML scraping.
One-line fix
How Google Cloud AutoML could lift its score

Add a per-unit price (e.g. $X / 1K calls) to the pricing page so an agent can compute its own cost before committing.

pricing_visible

true

headline_phrasing

AutoML beginner's guide Stay organized with collections Save and categorize content based on your preferences. — This beginner's guide introduces AutoML. To understand key differences between AutoML and custom training, see Choosing a training method.

tier_count

3

lowest_paid_entry_usd

null

free_tier

false

free_tier_terms

null

per_unit_price

null

annual_required

false

self_serve_paid_tiers

2

sales_only_tiers

0

public_api_docs_url

https://docs.cloud.google.com/docs

api_docs_auth_walled

false

ai_pricing_json_present

false

agents_txt_present

false

anonymous_purchase_path

false

per_unit_classification

null

usage_headline_present

false

custom_tier_present

true

agent_friendly

{"ai_pricing_json":false,"agents_txt":false,"llms_txt":false,"sitemap_xml":true,"mcp_server_card":false,"agent_skills_index":false,"x402_supported":false}

View raw extracted page text →
Page heading: AutoML beginner's guide Stay organized with collections Save and categorize content based on your preferences.
CTAs (40): Skip to main content · Technology areas · close · AI and ML · Application development · Application hosting · Compute · Data analytics and pipelines · Databases · Distributed, hybrid, and multicloud · Industry solutions · Migration
Skip to main content Technology areas close AI and ML Application development Application hosting Compute Data analytics and pipelines Databases Distributed, hybrid, and multicloud Industry solutions Migration Networking Observability and monitoring Security Storage Cross-product tools close Access and resources management Costs and usage management Infrastructure as code SDK, languages, frameworks, and tools / Console English Deutsch Español Español – América Latina Français Indonesia Italiano Português Português – Brasil עברית 中文 – 简体 中文 – 繁體 日本語 한국어 Sign in Vertex AI Start free Guides Reference Samples Support Resources Technology areas More Guides Reference Samples Support Resources Cross-product tools More Console Discover Overview Introduction to Vertex AI MLOps on Vertex AI Interfaces for Vertex AI Vertex AI beginner's guides Train an AutoML modelTrain a custom modelGet inferences from a custom model Train a model using Vertex AI and the Python SDK IntroductionPrerequisitesCreate a notebookCreate a datasetCreate a training scriptTrain a modelMake an inference Integrated ML frameworks PyTorchTensorFlow Vertex AI for BigQuery users Glossary Get started Set up a project and a development environment Install the Vertex AI SDK for Python Choose a training method Try a tutorial Tutorials overview AutoML tutorials Hello image data OverviewSet up your project and environmentCreate a dataset and import imagesTrain an AutoML image classification modelEvaluate and analyze model p…
You work at Google Cloud AutoML?
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Are you Google Cloud AutoML? Something off in this listing?
Agent-Ready Spec
Google Cloud AutoML
Approaching Agent-Ready

67

/ 100 (rubric v1.1)
Category

Machine Learning

Pricing model

Not advertised

Tier count

3

Free tier

No

Lowest paid entry

Sales-led

Self-serve / sales-only tiers

2 / 0

Public API docs

Public

Anonymous purchase path

No

Machine-readable pricing

Not published

Last refreshed

2026-05-06

Actions
Open live pricing page
Verdict reflects Approaching Agent-Ready status under rubric v1.1. Source observed at https://cloud.google.com/automl-tables/pricing.
Agent-friendly features1 of 7 present
Discovery files and protocols
Side-channel signals — informational, not part of the score. Each protocol is independent; adoption signals the publisher is thinking about agent buyers.

ai-pricing.json

agents.txt

llms.txt

sitemap.xml

MCP Server Card

Agent Skills

x402 / MPP

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