What you walk away with
Proactive management
Monitoring, patching and capacity management on the estate your AI retrieves from
Consolidation of the sprawl that accumulated during the build
Backup, recovery and retention verified rather than assumed
A named owner for an estate that currently has none
Performance
Query and retrieval performance tuned against real AI workloads
Index and partition strategy reviewed as volumes grow
Cost per workload tracked and reported
Bottlenecks found before your users find them
Governance held
Catalog, lineage and sensitivity kept current
Access reviews run on a schedule
Drift from the governance baseline flagged and fixed
A monthly report your steering group can read in ten minutes
How the cycle runs
Monthly - Management, tuning and a written report
Quarterly - Governance and cost review
Ongoing - Improvements agreed rather than assumed
Built for
Organizations that completed a Data Readiness build
Teams running Microsoft Fabric or Databricks in production
Anyone whose AI retrieves from an estate nobody owns
Regulated industries where governance drift becomes an audit finding
At a glance
Monthly
Proactive database management and consolidation
Performance tuning against retrieval workloads
Runs alongside Agent Assurance
Where it leads.
Keeps a Data Readiness build from decaying in the year after handover, which is when it usually does.
A foundation you built once still needs owning.
Monthly. Nothing drifts quietly.