Question 1

How does CastKit approach enterprise AI security and media data privacy?

Accepted Answer

CastKit's security approach covers data isolation, encryption, access controls, audit logs, retention, model policies, consent, and private deployment options. Each control is scoped to the customer account, with ownership divided between CastKit's platform responsibilities and the customer's operational responsibilities. Specific technical details are documented in the Privacy Policy and available for review during enterprise evaluation.

Question 2

How does CastKit isolate and encrypt media data?

Accepted Answer

Customer media files and workflow data are isolated at the account level - one customer's data is not accessible to another. Encryption applies to data in transit (using TLS) and at rest. Data boundaries extend across CastKit and any connected tools in your existing stack; customers retain responsibility for the security posture of third-party integrations they configure. Consult the Privacy Policy for the complete scope of encryption coverage.

Question 3

What access controls and audit logs does CastKit provide?

Accepted Answer

CastKit provides role-based access controls that determine which team members can view, edit, approve, or publish content across the portfolio. Administrative controls allow account owners to manage user permissions. Audit logs record approval actions, asset status changes, and ownership transfers so teams can review the history of every decision. Log access is available to authorized administrators within the platform.

Question 4

Does CastKit keep people in control of AI-assisted work?

Accepted Answer

Yes. CastKit presents AI as governed assistance - AI prepares the package, and the team approves it. AI drafts show notes, transcripts, chapter markers, newsletter copy, and social posts from approved audio. Every asset routes to the designated team member for review before publishing. Nothing publishes without a human sign-off. Approval history and ownership remain visible across the entire team at all times.

Question 5

What is CastKit's data retention policy?

Accepted Answer

Data retention periods and available controls are documented in CastKit's Privacy Policy. Enterprise customers can request information about deletion and export processes, including any documented exceptions, during the evaluation period. Specific retention timelines depend on the data type - media files, AI-generated outputs, and workflow records may carry different retention parameters. Contact CastKit for validated details applicable to your deployment.

Question 6

How does CastKit manage consent?

Accepted Answer

Consent management is part of CastKit's privacy approach and applies to media workflows involving guest recordings, community participants, and listener data. Consent status is recorded within the applicable workflow and remains visible to the team member responsible for that episode or asset. Who records consent and how it is stored depends on the workflow configuration; customers retain responsibility for obtaining consent from participants under applicable law.

Question 7

Does CastKit use customer media to train AI models?

Accepted Answer

CastKit processes customer media and workflow data to generate AI-assisted outputs such as show notes, transcripts, and social drafts. The validated policy covering model training, reuse, storage, and retention is published in the Privacy Policy. CastKit does not make unsupported claims about model training here; enterprise buyers should review the current Privacy Policy and direct specific questions to the CastKit team during evaluation.

Question 8

Where does CastKit require human review for AI-assisted work?

Accepted Answer

Human review is required before any AI-prepared asset can be published. AI prepares show notes, transcripts, chapter markers, guest research packages, newsletter drafts, and social posts from approved audio. Each asset routes to a designated team member for approval. Approved assets then move into distribution. No AI output is published without an explicit human approval step recorded in the workflow.

Question 9

Does CastKit offer private deployment options?

Accepted Answer

Private deployment options are available through CastKit's Private AI product, designed for enterprise teams with stricter data boundary requirements. Eligible configurations, data boundaries, operational ownership, and customer responsibilities vary by deployment type. Enterprise teams evaluating private deployment should contact CastKit to discuss configuration options, eligibility criteria, and the operational responsibilities that apply to each available approach.

Enterprise AI Security

Security and Privacy Controls

Data Isolation & Encryption

How does CastKit approach enterprise AI security and media data privacy?

How does CastKit isolate and encrypt media data?

Access Controls & Audit Logs

What access controls and audit logs does CastKit provide?

Does CastKit keep people in control of AI-assisted work?

Data Retention, Deletion & Consent

What is CastKit's data retention policy?

How does CastKit manage consent?

AI Model Policies

Does CastKit use customer media to train AI models?

Where does CastKit require human review for AI-assisted work?

Private Deployment Options

Does CastKit offer private deployment options?

Review CastKit's Security Documentation