Keep data access boundaries tight
Not every stakeholder, analyst, or AI tool should connect directly to production databases. Local execution helps teams keep the runtime closer to where the data already lives.
Product
Local execution for private-network data workflows.
DataPilot lets teams use local execution and on-prem workers to run trusted queries and scheduled exports close to protected databases while keeping one shared workflow for scheduling, notifications, downloads, and operational visibility.
Ideal for teams that cannot expose database access broadly across remote users, laptops, or third-party tools.
Why teams choose local execution and on-prem workers
Preserve one operational workflow
Keep the same loop for schedules, runs, notifications, and downloads even when execution happens inside a protected environment.
Support remote teams without broad network exposure
Reduce the need to give every user or external tool broad direct connectivity into private environments.
How it works
1. Configure once
Define the query workflow, schedule, and delivery logic in DataPilot. Teams keep one place to manage operational execution.
2. Execute near the database
Run the workload in the right environment instead of forcing every consumer to access the database directly.
3. Deliver outputs centrally
Keep notifications, download flows, and operational visibility in one shared product experience.
Use cases
Executive and operational reporting
Deliver recurring reports from protected systems without expanding raw database access across the company.
AI tools with safer execution boundaries
Support AI-driven workflows without turning direct database connectivity into the default pattern.
What stays valuable here
The hard part is not only generating SQL. Teams also need safe execution, delivery loops, visibility, and operational trust. That is where DataPilot becomes much more useful than a raw direct-connect setup.