Brilo AI can use audio call recordings as input to improve agent performance, but it does not automatically accept raw recordings for live model retraining without configuration and review. Brilo AI supports a workflow where recorded calls are transcribed, annotated, and ingested into a safe, controlled training dataset or used to update intent libraries and answer quality rules. Enabling audio ingestion typically requires explicit configuration, approved data handling, and a delivery method such as uploads to a secure storage location or an integration with your CRM or webhook endpoint. Brilo AI teams review data, apply labeling and quality controls, and then apply updates to voice agent behavior under change-control.

Can Brilo AI accept my recorded calls for training? — Yes. With configuration, Brilo AI can intake recordings that you supply, transcribe and annotate them, and use them to refine agent behavior.

Do you take raw audio and retrain instantly? — No. Brilo AI applies transcription, human review, and quality gating before training or deploying changes.

Can Brilo AI use call transcripts instead of audio? — Yes. Providing transcripts (speech-to-text) is a supported and often preferred path for faster review and safer annotation.

Enterprises ask if Brilo AI can ingest audio call recordings directly for training because many regulated teams already capture calls for quality and compliance. Buyers want to know whether those existing recordings can be reused to speed up model improvements, reduce annotation effort, and personalize the Brilo AI voice agent to their domain. Procurement, security, and compliance leaders also raise questions about data handling, access controls, and whether training will expose sensitive customer information. Technical teams want clarity on file formats, metadata, and integration points with their storage or CRM.

When enabled, Brilo AI implements a controlled pipeline to turn audio recordings into training signals. Typical steps include secure upload, transcription (speech-to-text), annotation or labeling, quality review, and then controlled updates to intent libraries or response templates. Call recording ingestion is an optional workflow that can be configured to accept audio files from secure storage or via your webhook endpoint. A training dataset is the collection of transcribed and labeled interactions that the voice agent uses to refine recognition, routing, or response selection.

Brilo AI’s self-learning capabilities can incorporate these datasets under change-control rather than open-ended retraining; see the Brilo AI self-learning agent overview for how continuous learning and behavior updates are handled: Brilo AI self-learning agent overview.

Key technical terms you may see in the workflow include transcription, annotation, supervised learning, intent library, model update, and quality gating.

Brilo AI enforces safety and operational guardrails before any audio-derived data changes agent behavior. Examples of guardrails:

Quality gating is the automated and human review process that verifies annotations meet agreed accuracy thresholds before updates are applied. Brilo AI also supports routing changes that are limited by configured intent confidence thresholds so the agent will not assume new behaviors when confidence is low.

For general guidance on how Brilo AI analyzes calls and what to expect from automated call analysis, see Brilo AI’s call analysis overview: Brilo AI call analysis overview.

Healthcare example:

A hospital’s patient access team provides a sample set of recorded scheduling calls to Brilo AI. Brilo AI transcribes and redacts personal health information, annotates intents like appointment scheduling and insurance verification, and updates the agent’s scripts so the Brilo AI voice agent handles routine scheduling queries more accurately. The process includes clinical-data controls and human review before deployment.

Banking / Financial services example:

A bank supplies recorded customer service calls about balance inquiries and fraud reporting. Brilo AI ingests the audio, produces transcripts, and expands the agent’s intent library for dispute routing while keeping transaction-identifying details masked. Updated routing rules are staged and tested in a non-production environment before being pushed live.

Insurance example:

An insurer shares claims intake recordings so Brilo AI can better recognize claim types and required fields. Brilo AI uses annotated transcripts to improve form-filling accuracy and triage routing to the correct claims team.

Brilo AI voice agent workflows can hand off to a human agent when configured confidence thresholds are not met or when specific escalation triggers are detected. Typical handoff behaviors:

Human handoff is a workflow step that transfers call state and conversation context from the Brilo AI voice agent to your live agent or another workflow, preserving transcripts and labels for continuity.

For integration patterns and call logging options, review Brilo AI’s integration notes for CRM and call logging to understand how recordings and metadata are captured and associated with customer records: Brilo AI HubSpot integration and call logging.

For guidance on using Brilo AI as an answering and intake system that feeds these processes, see the AI phone answering system overview: AI phone answering system overview.

Using recorded calls to refine Brilo AI voice agents can improve first-contact resolution, reduce repeat transfers, and increase routing accuracy. Organizations gain:

These outcomes rely on disciplined data handling, annotation quality, and a staged release process — not on instant, unmoderated retraining.

Can I send raw audio files to Brilo AI?

Yes, Brilo AI can accept raw audio files if you configure an intake path and agree on handling and review processes. Brilo AI will typically transcribe and apply redaction or annotation workflows before any training use.

How long does it take for recordings to influence agent behavior?

The timeline depends on transcription and annotation throughput, review cycles, and your change-control schedule. Expect an iterative timeline rather than immediate updates because human review and quality gating are required.

What file formats and quality do you support?

Brilo AI commonly accepts standard audio formats and requires recordings with sufficient clarity for reliable transcription. Specific format guidance will be provided during setup; if needed, Brilo AI can provide recommended encoding and sample-rate settings.

Will Brilo AI keep my audio and transcripts secure?

Brilo AI applies access controls and can limit storage and viewing to authorized roles. Data retention, redaction, and secure transfer practices are configurable as part of the ingestion setup. Discuss your specific compliance requirements during setup.

Can Brilo AI train on only parts of a call (e.g., agent script only)?

Yes. Brilo AI can be configured to segment calls, extract only caller or agent turns, or redact portions prior to annotation, depending on your policies and annotation guidelines.

Training with audio recordings is available under a controlled, review-based workflow; contact your Brilo AI representative to start a pilot and review data handling and compliance options.