Brilo AI’s Data Retention and Deletion Policy - V3 should be evaluated for how it implements retention schedules, handles deletion and data subject requests, and documents exceptions. Ask whether Brilo AI enforces tenant-specific retention schedules, how deletion is executed (logical vs. physical), what audit logs and proof of deletion are provided, and which legal or fraud-detection exceptions prevent deletion. Also confirm who owns usage telemetry versus customer-submitted data and how Brilo AI surfaces retention configuration and evidence for audits.

What should a DPO ask about data lifecycle management? — Confirm retention schedules, deletion mechanics, exception handling, and proof-of-deletion logs from Brilo AI.

How do I verify Brilo AI deletes customer data on request? — Request documented deletion workflows, deletion proofs, and an explanation of any lawful-retention exceptions.

What evidence will Brilo AI provide for compliance audits? — Ask for audit trails, access logs, and retention configuration exports that show policy enforcement.

Enterprises ask these questions because regulated environments require clear, demonstrable control over the entire data lifecycle. A DPO needs to know not only that Brilo AI can delete data, but that deletion is repeatable, auditable, tenant-scoped, and aligned to the organization’s retention schedule. Buyers also need to understand exceptions — for example when a vendor must retain records for legal holds or fraud investigations — and how those exceptions will be documented during audits.

Key procurement concerns include data ownership, evidence for deletion, support for data subject requests, segregation of usage telemetry from customer data, and the ability to map Brilo AI call data back to enterprise retention rules.

Brilo AI implements retention and deletion as a configurable lifecycle that applies to customer-submitted call data, transcripts, and derived metadata. Retention is typically enforced by tenant-level configuration that maps content categories (recordings, transcripts, sentiment metadata) to retention schedules and deletion rules.

Subscriber Data is customer-submitted information (for example, call recordings and transcripts) that your organization controls for retention and deletion.

Usage Data is operational telemetry and system metrics that Brilo AI may collect and use separately from Subscriber Data.

A Deletion Request is a request—initiated by you or a data subject—that triggers Brilo AI to remove or render inaccessible the specified Subscriber Data according to the configured retention policy.

Brilo AI’s lifecycle typically includes classification, scheduled retention enforcement, on-demand deletion (data subject request), and logging/audit-trail generation. Brilo AI may separate short-term caches, active indexes, and long-term archived storage; each layer may follow different deletion semantics (logical vs. physical). Ask Brilo AI to describe the end-to-end flow for your tenant’s data.

Brilo AI enforces guardrails and recognizes specific boundaries where deletion may be prevented or delayed. Typical exceptions include legal holds, subpoenas, fraud detection needs, and other lawful obligations. Brilo AI’s privacy and terms indicate there are circumstances where Brilo AI will not delete personal information if retention is required by law or for fraud prevention.

A Retention Exception is a documented condition that pauses deletion for legal, compliance, or security reasons.

Ask Brilo AI for explicit escalation criteria that convert a deletion action into a retention exception and for the mechanism that records and timestamps those exceptions.

Healthcare example: A clinic using Brilo AI for appointment reminders should confirm how long call recordings and sensitive identifiers are retained, who can request deletion, and how deletion requests for patient contacts are executed and logged without disrupting service continuity.

Banking / Financial services / Insurance example: A retention manager in an insurer using Brilo AI for policy retention calls should verify that retention schedules for calls tied to claims or cancellations are enforced per policy, that Brilo AI can tag recordings with case IDs, and that deletion requests do not inadvertently remove records required for dispute resolution or compliance investigations.

Technical terms to look for during evaluation: data lifecycle management, retention schedule, deletion audit trail, access logs, data subject request, data minimization, anonymization.

Brilo AI voice agent workflows can escalate to humans or to admin workflows when a retention or deletion question arises. Typical handoff behaviors include:

Confirm with Brilo AI how handoffs are recorded, who receives alerts, and whether handoff triggers are configurable by tenant or workflow.

These steps ensure Brilo AI can map its retention engine to your policies and provide the necessary operational evidence for audits.

These are operational outcomes you can validate through documentation, test deletion requests, and review audit logs.

What is the difference between logical and physical deletion?

Logical deletion makes data inaccessible to users (and often to search/indexing) but may leave data remnants in backups; physical deletion removes the data from storage media according to Brilo AI’s deletion procedures. Ask Brilo AI which method applies to each storage tier.

How long does Brilo AI take to process a deletion request?

Processing time depends on the configured retention workflow and any active exceptions. Ask Brilo AI for target SLAs for on-demand deletion and for exception handling timelines.

Can Brilo AI prove a record was deleted?

Brilo AI can generate audit entries that show deletion actions, timestamps, and the responsible actor; confirm the exact proof artifacts Brilo AI will supply for your audits.

Will Brilo AI retain metadata after deletion?

Some metadata used for system operation or telemetry may be retained as Usage Data. Confirm which metadata types Brilo AI treats as Subscriber Data versus Usage Data.

How are legal holds handled?

Legal holds should be documented and prevent scheduled deletion; Brilo AI should record the hold, its scope, triggering condition, and the approver. Ask for the workflow that creates and lifts holds.