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Genai For Marketing

Genai For Marketing is a public Google Cloud repository containing a deployable generative-AI marketing application, frontend and backend code, Terraform infrastructure, templates and Jupyter notebooks. Its examples cover marketing-content generation, natural-language-to-GoogleSQL analysis, trend and news summarization, content search, campaign insights and transfer of generated assets to Google Workspace.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Genai For Marketing — OpenViST project profile in AI Developer Tools & SDKs.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when you need an implementation reference for a Google Cloud marketing-AI application, with deployable frontend, backend and infrastructure materials rather than only conceptual examples.

Who it is for

  • Marketing teams exploring data and campaign insights.
  • Content teams generating marketing copy and visual assets.
  • Developers building or adapting Google Cloud generative-AI applications.
  • Teams studying Vertex AI and Gemini-related marketing workflows.

Documented uses

  • Generate blog posts, website articles, email copy, social-media posts and Performance Max assets.
  • Translate natural-language marketing questions into GoogleSQL for BigQuery.
  • Visualize marketing data through Looker dashboards.
  • Analyze Google Trends data and summarize related news.
  • Search business content with Vertex AI Search.
Before you choose

Requirements & limits

The repository is public and accessible on GitHub. It is licensed under Apache-2.0. The supplied material does not specify pricing or account requirements.

  • Terraform is the documented deployment route.
  • The repository combines application code with notebooks and infrastructure, making it relevant to builders as well as users studying the workflows.
  • Natural-language-to-GoogleSQL is included alongside content generation, search and dashboard-based analysis.
  • The examples depend on Google Cloud services and integrations such as Vertex AI, BigQuery, Looker and Google Workspace.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Deploy the marketing application with Terraform

Set up the repository’s Google Cloud marketing-AI solution using its documented deployment path.

Before you start

  • Access to the public repository.
  • A Google Cloud environment suitable for the repository’s Terraform deployment instructions.
  • The repository’s deployment guide in /infra/README.md.

Steps

  1. Review the repository structure and the application architecture materials.

  2. Follow the step-by-step deployment instructions in /infra/README.md.

  3. Use the repository’s frontend, backend APIs and infrastructure configuration as the deployment components.

  4. Review the demonstrated marketing workflows, including content generation and natural-language-to-GoogleSQL analysis.

Expected outcome

A deployed solution implementing the repository’s described marketing generative-AI capabilities.

Guide limitations

  • The supplied material does not specify account, billing, permission or service-configuration prerequisites.
  • Source-based guidance does not establish that deployment or individual integrations have been executed successfully.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
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Sources checked
4 October 2026
Original website title
GoogleCloudPlatform/genai-for-marketing · Official homepage title · retained in its source language
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