Data boundaries for a local-first AI workflow
Local-first describes where you prefer work to happen; it does not prove that no data leaves the machine. Trace model downloads, extensions, remote nodes and logs, then classify the information crossing each boundary before using sensitive inputs.
Classify the inputs and outputs
Identify public material, internal work, personal information and confidential client assets separately. Record who is allowed to process and receive each class. Include generated outputs that may reveal sensitive inputs; a transformed image or summary is not automatically safe to share.
Use an ordinary permitted sample for initial tests. Avoid placing secrets in prompts, filenames or graph notes. If a workflow must handle sensitive data, review that requirement before testing it through an unfamiliar extension or hosted interface.
Trace external dependencies
List model downloads, package installation, remote inference, monitoring and storage calls. A local ComfyUI interface can contain nodes that contact external services. Inspect the particular graph and extension configuration rather than treating the application's name as a complete network description.
Separate setup-time downloads from runtime transfer of inputs. Both should be understood, but they have different implications. Record the destination, purpose and data category for every necessary external route, and remove unnecessary transmission from the design where practical.
Read the applicable handling policy
OpenAI's business-data and API data-controls documentation distinguish product and endpoint handling. Use the documentation for the actual service being called. Do not generalise a training default into a claim that no logs, application state or other retained data can exist.
Keep the policy date and account configuration with the project record. Refer legal or regulatory questions to the responsible qualified reviewer. This page provides a technical inventory method, not a declaration that a particular deployment is compliant with every jurisdiction or contract.
Verify the intended boundary
Test the configured route with non-sensitive inputs and inspect the available network and application logs. Confirm that outputs can be retrieved and deleted through the documented process. Keep credentials out of shared workflow files and public bug reports.
Record limitations that cannot be verified from the application side rather than substituting a marketing claim. This revision withdraws the earlier blanket extraction narrative and replaces it with a concrete data-boundary review. A privacy statement should describe the verified route and remaining assumptions, not rely on whether a model is labelled local or open.