genai-for-marketing and genai-factory

These are complementary tools where genai-for-marketing provides application-level generative AI implementations that would deploy using the infrastructure blueprints and IaC patterns defined in genai-factory.

genai-for-marketing
61
Established
genai-factory
53
Established
Maintenance 10/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 10/25
Adoption 10/25
Maturity 15/25
Community 18/25
Stars: 470
Forks: 143
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
Stars: 121
Forks: 22
Downloads:
Commits (30d): 0
Language: Python
License: Apache-2.0
No Package No Dependents
No Package No Dependents

About genai-for-marketing

GoogleCloudPlatform/genai-for-marketing

Showcasing Google Cloud's generative AI for marketing scenarios via application frontend, backend, and detailed, step-by-step guidance for setting up and utilizing generative AI tools, including examples of their use in crafting marketing materials like blog posts and social media content, nl2sql analysis, and campaign personalization.

This project helps marketing teams streamline their daily tasks using Google Cloud's generative AI. It takes marketing data, natural language questions, and content requests to produce marketing insights, SQL queries, trend analyses, and ready-to-use marketing materials like blog posts and social media content, even integrating with Google Workspace. It's designed for marketing managers, analysts, and content creators.

marketing-automation content-creation market-research marketing-analytics campaign-management

About genai-factory

GoogleCloudPlatform/genai-factory

A collection of end-to-end infrastructure blueprints to deploy generative AI infrastructures in GCP, using IaC and following security best-practices.

This project offers ready-to-use blueprints for setting up generative AI tools on Google Cloud, ensuring they follow security best practices. It takes your configuration inputs and provides fully deployed AI infrastructures such as RAG systems, AI search engines, or natural language query tools. This is ideal for cloud architects and AI solution developers who need to quickly deploy secure and compliant generative AI applications.

AI deployment Cloud infrastructure Generative AI Security best practices RAG systems

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