System
AI on top of data warehouses and databases
Data warehouses and databases hold the clean, joined-up view of the business. AI is useful where it makes that data answerable, surfaces anomalies and reduces the work of producing reports and checks.
Who this is for
Heads of data, analytics leads and finance/operations leaders using Snowflake, BigQuery, Synapse, Postgres or similar.
Common problems we see
- Slow turnaround on ad-hoc data questions.
- Reporting that does not catch anomalies in time.
- Manual reconciliation across sources.
- Unclear ownership of definitions and metrics.
Useful workflows
- Reporting and insight workflows.
- Reconciliation and checking workflows.
- Monitoring and alerting on key metrics.
- Search and retrieval against structured data.
What WithPraxis might build
- Governed question-answering tools on top of your warehouse.
- Anomaly detection on key metrics.
- Reconciliation tools across sources.
- Self-service reporting that respects existing models and access controls.
Governance and control
AI use respects existing access controls and definitions. Outputs are traceable to the underlying data. Changes are reviewable.
Where this connects