Data minimization
Each project should identify the minimum data needed for the workflow instead of copying broad enterprise datasets by default.
Enterprise AI should be evaluated with clear data boundaries before launch.
Fikir Yazilim's products touch ERP data, production visuals, catalogues and browser workflows. Before a deployment, the team defines data access, permissions, logging and operational responsibility with the customer.
Permission mapping
ERP, reporting and browser automation workflows should respect company roles, access rules and approval paths.
Observable automation
AI-assisted actions should remain visible and reviewable, especially for browser automation and operational reporting.
Deployment fit
Cloud, private network and customer-specific deployment options are evaluated according to data sensitivity and integration scope.
Discovery checklist
Security review topics before production use
The exact implementation depends on product scope. These topics should be clarified before moving from demo to live operation.
- Which ERP tables, reports, catalogues or browser workflows are in scope
- Who can access which data, dashboards and automation outputs
- How credentials, sessions and audit records are handled
- Whether cloud, private network or customer-specific deployment is required
- How support, incident response and change management will work
Does Fikir Yazilim need full ERP access?
No default assumption should be made. ERP access should be limited to the data and permissions required by the selected workflow.
Can deployment be evaluated for private environments?
Yes. The deployment model should be reviewed according to customer security requirements, integration scope and operational constraints.
How should AI browser automation be governed?
Browser automation should use controlled sessions, visible steps and clear policies for credentials, approvals and auditability.