Security

Security posture and AI workflow boundaries

The working standard is simple: use the minimum data needed, keep buyer-facing AI human-reviewed, and document the workflows before scaling automation.

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Principles

Security starts with controlled workflows

dialGTM work should favor scoped access, human review, clear data flows, and practical QA before automation touches buyer-facing communication.

Map the data needed for each workflow before connecting tools

Keep humans in approval loops for buyer-facing communication

Avoid fully autonomous outbound unless explicitly approved

Document workflow owners, handoffs, and QA expectations

Data

Data handling boundaries

Before an engagement, prospective clients should avoid sending sensitive credentials, private customer exports, or regulated data through public forms or email. Project-specific data handling should be defined in the engagement process.

Use least-privilege access where client systems are involved

Prefer sample or redacted data for early workflow design

Keep approval rules explicit for AI-generated outputs

Remove access when work no longer requires it

Claims

No unverified compliance claims

This page is a trust overview, not a compliance certificate. Do not add SOC 2, ISO, HIPAA, GDPR, or vendor-security claims unless they are verified and approved.

No invented certification claims

No implied legal guarantees

No customer system details without approval

No sensitive client architecture published as proof