Compare the Top Agentic Data Management Apps for Android as of August 2026

What are Agentic Data Management Apps for Android?

Agentic data management platforms use autonomous AI agents to manage, govern, and optimize data across complex enterprise environments. They can discover data assets, monitor data quality, and take action to resolve issues such as schema drift, access violations, or pipeline failures. These platforms reason over metadata, usage patterns, and policies to automate decisions that traditionally require human intervention. Many agentic data management platforms integrate with data warehouses, lakes, and analytics tools to operate across the full data lifecycle. By reducing manual effort and improving reliability, they help organizations maintain trusted, scalable, and well-governed data systems. Compare and read user reviews of the best Agentic Data Management apps for Android currently available using the table below. This list is updated regularly.

  • 1
    Domo

    Domo

    Domo

    Domo puts data to work for everyone so they can multiply their impact on the business. Our cloud-native data experience platform goes beyond traditional business intelligence and analytics, making data visible and actionable with user-friendly dashboards and apps. Underpinned by a secure data foundation that connects with existing cloud and legacy systems, Domo helps companies optimize critical business processes at scale and in record time to spark the bold curiosity that powers exponential business results.
  • 2
    Auraa

    Auraa

    Covasant Technologies Private Limited

    Auraa is Covasant's Databricks-native, agent-driven data platform which is the fastest path to AI-ready data on Databricks. With its conversational AI capabilities in natural language, enterprises can use agents to discover various data sources, build pipelines, enforce data quality, and register everything in Unity Catalog autonomously, from day one. Auraa eliminates pipeline code, engineering backlog, and months of manual configuration. While creation of a data lake on Databricks usually takes more than 18-24 months, Auraa onboards the first source in under 15 minutes, deploys the first use case within hours, and shrinks the overall deployment timeframe to about 8-10 weeks, and reduces the overall implementation cost by upto 70%. Auraa treats every data engineering decision as structured, versioned, governed metadata rather than fragile hand-coded pipelines. Auraa ensures Databricks lakehouse is reproducible, auditable, and continuously improvable by agents.
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