Use case: Security

Run the security scan without the egress tax

Security configuration scans become one-click templates. Because every AI model runs locally, scan content, credentials, and hostnames never leave the estate.

Why security teams pick Flow

Built for the environments that say no to cloud AI

Zero-egress inference

No inference data leaves the workstation. There are no cloud data processing agreements, no third-party inference audits, and no data-residency reviews to block adoption.

Credential isolation

The orchestration engine is the sole credential custodian. No AI model ever sees a password, token, or connection string. This is enforced by the architecture, not by policy.

PII sanitization

Credentials, hostnames, dataset names, IPs, and job-card identifiers become typed placeholders before any text reaches a model.

Sandboxed execution

Shell steps run with pinned working directories, environment allow-lists, output caps, and timeouts. An opt-in OS sandbox profile is also available on macOS.

Audit-grade history

Every run is recorded. Every shell invocation writes a JSON audit line. Every AI suggestion and user decision lands in the execution history.

Destructive-action gates

Runs pause before any node that deletes files, force-pushes, or removes infrastructure. This is on by default, and each step is confirmed on its own.

Read the isolation architecture

Domain segmentation, credential custody, the PII sanitizer, and the compliance implications are documented in full.