Indicium Launches AI Data Squads for AI-Ready Data Migration
Indicium introduces AI Data Squads, a service combining AI agents and human expertise to streamline data migration for AI applications, built on the IndiMesh framework.
New York-based AI and data consulting firm Indicium has unveiled its new AI Data Squads service, designed to help businesses manage complex data modernization and migration projects. The service, built on the company’s IndiMesh framework, combines AI agents with human expertise to accelerate data transformation for AI-ready platforms, with an initial focus on Databricks and dbt Labs.
The Need for AI-Ready Data
According to Daniel Avancini, Indicium’s Chief Data Officer, many enterprises struggle to adopt advanced AI due to outdated data systems. “Most companies understand they can’t do advanced AI use cases because their data platforms aren’t ready,” Avancini told CRN. “They lack governance, security, or the technology to provide AI-ready data.”
How AI Data Squads Work
Each AI Data Squad includes:
- Human engineers and consultants
- AI agents for automation and optimization
- IndiMesh framework for scalable solutions
The service aims to reduce migration times by 90%, according to early results. It automates tasks like project planning, data validation, and optimization, ensuring faster and higher-quality outcomes.
Expansion Plans
While initially targeting Databricks and dbt Labs, Indicium plans to expand the service to other platforms. The launch coincides with Databricks’ Data + AI Summit in San Francisco this week.
Related News
- Meeting The Data Needs Of The AI World: The 2025 CRN Big Data 100
- Indicium Targets AI Data Asset Governance with New Databricks Solution
Key Takeaways
- Indicium’s AI Data Squads blend AI and human expertise for data migration.
- The service is built on the IndiMesh framework, launched in April 2025.
- Early adopters have seen 90% faster data migration.
- Focus industries include financial services, capital markets, and pharmaceuticals.
For more details, visit Indicium’s website.
Related News
Data Scientists Embrace AI Agents to Automate Workflows in 2025
How data scientists are leveraging AI agents to streamline A/B testing and analysis, reducing manual effort and improving efficiency.
Agentic AI vs AI Agents Key Differences and Future Trends
Explore the distinctions between Agentic AI and AI agents, their advantages, disadvantages, and the future of multi-agent systems.
About the Author

Alex Thompson
AI Technology Editor
Senior technology editor specializing in AI and machine learning content creation for 8 years. Former technical editor at AI Magazine, now provides technical documentation and content strategy services for multiple AI companies. Excels at transforming complex AI technical concepts into accessible content.