Simon Data launches AI-powered marketing agents for seamless personalization
Simon Data introduces Composable AI Agents for marketers, powered by Snowflake Cortex AI and Claude, enabling data-driven personalization without coding.
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AI-Powered Marketing Transformation
Simon Data has unveiled Composable AI Agents, a groundbreaking suite of marketing tools built on Snowflake Cortex AI and powered by Claude from Anthropic. This innovation aims to empower marketers with direct, governed access to customer data for personalization—eliminating the need for coding or data team dependencies.
Solving Key Marketing Challenges
The platform addresses two critical pain points:
- Lack of visibility into missing data
- Difficulty identifying subtle behavioral patterns
By surfacing both existing data and new contextual signals, the system enables instant activation across marketing campaigns.
Three Types of AI Agents
- Insights Agents: Analyze customer interactions to identify high-impact campaign opportunities
- Data Agents: Transform contextual data into actionable attributes via AI-generated 'Smart Fields'
- Automation Agents: Create and optimize adaptive micro-targeted campaigns
Seamless Platform Integration
The AI agents automatically feed data into popular customer engagement platforms including:
Executive Perspective
"Marketers have been told for years that personalization was solved," said Jason Davis, CEO of Simon Data. "The reality has been static segments, brittle workflows, and missed customer moments. Composable AI Agents shift that reality, giving marketers direct access to context, decisioning, and execution."
The Future of Marketing
This launch represents a paradigm shift in marketing technology, offering:
- Faster campaign execution
- Deeper customer insights
- Greater marketer control
The solution promises to enable personalized, contextually relevant marketing at scale, potentially redefining industry standards for data-driven campaigns.
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About the Author
Dr. Sarah Chen
AI Research Expert
A seasoned AI expert with 15 years of research experience, formerly worked at Stanford AI Lab for 8 years, specializing in machine learning and natural language processing. Currently serves as technical advisor for multiple AI companies and regularly contributes AI technology analysis articles to authoritative media like MIT Technology Review.
