Happy to share a quick update with the community on the progress we’ve made with our on-premise AI agent integration into Ataccama ONE.
We’ve now developed and tested four distinct use cases that support users across various data governance tasks. All of these are accessible through a lightweight chat-based interface that runs alongside the Ataccama UI, without modifying the core product.
Here’s a brief overview of what’s working today:
Data Quality Insights
The agent detects data quality issues and provides root cause analysis with natural-language explanations. When needed, it also offers recommendations for resolving common problems, making DQ monitoring faster and more intuitive.
AI-Assisted Data Catalog Navigation
Users can search and explore the Ataccama catalog using natural language. The agent retrieves relevant metadata and provides contextual recommendations, helping non-technical users find and understand data without needing to know the structure.
Compliance & Sensitive Data Discovery
The agent helps compliance teams identify and classify sensitive data across systems. It offers real-time audit visibility and generates draft reports to support regulatory readiness, reducing manual review and documentation.
Metadata Enrichment
By analyzing table and column structures, the agent auto-generates business-friendly descriptions for metadata elements. It doesn’t stop at suggestions — it can also write these enriched descriptions directly into the Ataccama metadata repository, updating the relevant description fields of tables and attributes. This significantly reduces manual documentation effort and improves metadata consistency across the platform.
All use cases are powered by our own on-prem LLM and fully isolated from external cloud services. We’ve designed the logic to integrate with Ataccama via available interfaces, making the experience seamless while keeping the platform intact.
Looking forward to hearing thoughts from the community and continuing to share our journey as it evolves.
