genai-for-marketing and genai-on-google-cloud

These are ecosystem siblings where A provides domain-specific marketing implementations and guidance built on top of the broader enterprise GenAI systems and patterns that B documents for Google Cloud.

genai-for-marketing
61
Established
genai-on-google-cloud
46
Emerging
Maintenance 10/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 10/25
Adoption 5/25
Maturity 15/25
Community 16/25
Stars: 470
Forks: 143
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
Stars: 14
Forks: 7
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
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-on-google-cloud

ayoisio/genai-on-google-cloud

GenAI on Google Cloud: Enterprise Generative AI Systems and Agents

This project provides practical, hands-on guidance for building and deploying advanced generative AI systems and agents on Google Cloud. It teaches you how to take large language models from concept to reliable production applications. You'll learn how to feed these systems with prepared data and build intelligent agents that can process various data types. This is ideal for AI/ML engineers, data scientists, and solution architects responsible for developing and managing enterprise-grade AI solutions.

enterprise-ai llm-application-development mlops agent-systems google-cloud-ai

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