AI transformation begins with data transformation
Managing data workflows is labor-intensive and error-prone, causing pipeline disruptions, data inaccuracies and delayed analytics. Emergence tackles the messy data problem by building agents that connect, monitor, and address data issues before they impact your business.
Problem statement
Enterprise data is deeply fragmented
data unused for analytics
Scaling Generative AI for Value: Data Leader Agenda for 2025, Forrester
citing the need to manage unstructured data as a problem for their business
Scaling Generative AI for Value: Data Leader Agenda for 2025, Forrester
What Emergence brings
Autonomous agents that produce, consume, and act on enterprise data continuously, at scale.
Data readiness
Connect disparate data and AI assets
Connect your data sources to enable automated analysis and monitoring. Our solution continuously assesses metadata and overall data quality, detecting and acting on data drifts before they impact your business.
Data readiness
Identify data violations
Automatically generated scorecards surface key metadata insights and data quality issues—highlighting risks, inconsistencies, and areas requiring action. Align scorecards to your business' internal policies and guidelines.
Data readiness
Run recommended SQL scripts
Execute system-generated SQL scripts to resolve identified issues. Review suggested fixes, validate changes, and apply them directly to your data.
