Direct Answer (TL;DR)
Brilo AI can be configured to push call data to a custom database using an outbound API or webhook integration as part of a Custom Database Call Data Push. Brilo AI voice agent can emit structured call events (JSON payloads) after or during a call—transcripts, call metadata, dispositions, and sentiment—so your systems can ingest and store them in your database. Configuration typically requires a reachable webhook or API endpoint on your side, an agreed payload schema, and routing rules set in Brilo AI. This setup supports use cases like CRM syncing, audit logging, and analytics pipelines.
Can Brilo AI send call records to our database? Yes — Brilo AI can push call records and structured call payloads to your webhook or API endpoint for ingestion.
Can Brilo AI export transcripts and metadata to a custom DB? Yes — Brilo AI can deliver transcripts, timestamps, and metadata in a JSON payload for your ingestion pipeline.
Does Brilo AI support scheduled bulk exports to a database? When enabled, Brilo AI can deliver batched or event-driven exports via webhooks or APIs depending on your agreed workflow.
Why This Question Comes Up (problem context)
Enterprise buyers ask about Custom Database Call Data Push because they must centralize call records for compliance, reporting, and downstream analytics. Healthcare, banking, and insurance teams often need certified storage, searchable call logs, or integration with internal risk and case-management systems. Buyers also want to avoid manual entry and preserve data fidelity (timestamps, agents, dispositions, and call transcripts) so downstream models and auditors can rely on consistent datasets.
How It Works (High-Level)
When you enable a Custom Database Call Data Push, Brilo AI voice agent emits call events to your configured endpoint according to routing and delivery rules. Typical behavior:
Brilo AI generates a structured JSON payload for each call event (call start, call end, transcript available, disposition, etc.).
Brilo AI delivers the payload to your webhook endpoint or calls your API with authentication and retry logic.
Your endpoint validates the payload and writes the data into your custom database or event store.
In Brilo AI, call payload is the structured JSON message Brilo AI sends with call metadata, transcript, and agent actions.
In Brilo AI, webhook endpoint is your publicly reachable URL that receives Brilo AI call events for ingestion.
In Brilo AI, call session record is the stored object representing a single call lifecycle including timestamps, transcript, and resolution data.
Guardrails & Boundaries
Brilo AI is governed by configurable guardrails to protect data quality and avoid unsafe behavior. Typical guardrails include:
Rate limits and backoff: Brilo AI will retry failed deliveries with backoff but will stop after configured retry thresholds to avoid endless retry storms.
Payload size limits: Brilo AI will truncate or provide transcript references if payloads exceed agreed limits.
Sensitive-data handling: Brilo AI will follow configured redaction or suppression rules for PII before sending payloads when those rules are enabled.
Event filtering: You can scope which events Brilo AI pushes (for example, only post-call transcripts, or only calls with certain dispositions).
In Brilo AI, redaction rule is a configured filter that removes or masks sensitive fields in outbound payloads before delivery.
What Brilo AI will not do without configuration:
Brilo AI will not write directly into a private database behind a firewall without a reachable API or middleware to accept events.
Brilo AI will not change your database schema; you must map or transform Brilo AI payloads on your side.
Applied Examples
Healthcare example:
A hospital configures Brilo AI voice agent to push post-call transcripts and encounter metadata to an internal clinical data store via a secure webhook. Brilo AI applies configured redaction rules to remove specified patient identifiers before sending the payload, and your ingestion service maps the payload to the EHR audit table.
Banking/financial services example:
A retail bank routes Brilo AI call dispositions and call sentiment scores to an internal fraud analytics pipeline. Brilo AI emits call session records to the bank’s webhook endpoint in JSON; the bank ingests these records into its event stream for real-time risk scoring.
Insurance example:
An insurance carrier has Brilo AI push claim-related call transcripts and key-value extractions (policy number, claim type) to the claims management database for immediate case creation and audit logging.
Human Handoff & Escalation
Brilo AI voice agent workflows can trigger a human handoff or escalate to alternative workflows before or after pushing data:
During a call: Brilo AI can flag an escalation event in the outbound payload and simultaneously call a configured escalation webhook, allowing your systems to notify live agents or create priority tickets.
After a call: A post-call payload can include a handoff token or a follow-up flag. Your backend can then route the record to a live agent queue, create a task in your CRM, or trigger an email/SMS alert.
Fallbacks: If Brilo AI cannot deliver a payload after retries, you can configure it to store the event temporarily and send an alert to your operations team for manual reconciliation.
Setup Requirements
Provide a reachable webhook endpoint or API endpoint that accepts HTTPS POST requests and verifies an authentication header or token.
Define a payload schema (JSON) that maps Brilo AI fields (transcript, start/end timestamps, caller ID, disposition, sentiment) to your database columns.
Configure authentication by exchanging an API key, JWT, or other agreed scheme with your Brilo AI implementation team.
Specify routing rules to determine which call events to push (all calls, only answered calls, or calls with specific dispositions).
Implement inbound validation and idempotency handling on your endpoint to avoid duplicate records.
Test delivery using a staging webhook and sample Brilo AI payloads before enabling production delivery.
Monitor delivery logs and configure alerts for failed deliveries or exceeded rate limits.
Business Outcomes
Key outcomes from implementing a Custom Database Call Data Push include:
Centralized records: Brilo AI call events stored in your database give a single source of truth for reporting and audits.
Faster workflows: Automated post-call pushes reduce manual entry and accelerate follow-up actions in healthcare and claims workflows.
Better observability: Ingesting transcripts and metadata enables analytics, quality reviews, and model training using real conversation data.
Controlled data flow: Configurable redaction and event filtering help you meet internal privacy and governance standards.
FAQs
What types of call data can Brilo AI push to our database?
Brilo AI can push structured call metadata (timestamps, caller/callee IDs), call transcripts, dispositions, confidence scores, extracted key fields (entities), and sentiment metadata in JSON payloads for ingestion.
Can Brilo AI push data in real time during a live call?
Yes—when configured, Brilo AI can emit interim events (for example, partial transcripts or detection events) during a live call, but you should confirm payload frequency and size limits with your Brilo AI implementation team.
How does Brilo AI authenticate when sending data to our endpoint?
Authentication is configurable; common patterns include API keys, signed headers, or bearer tokens exchanged with your Brilo AI account team. Your endpoint must validate the token to accept payloads.
What happens if our endpoint is down when Brilo AI tries to deliver a payload?
Brilo AI will retry deliveries according to configured retry/backoff policies and will log failures. You can configure notification thresholds and a dead-letter process for manual reconciliation.
Can Brilo AI redact sensitive data before pushing to our database?
Yes—Brilo AI supports configurable redaction rules and field suppression. Work with your Brilo AI contact to define which fields to redact or mask before delivery.
Next Step
Contact your Brilo AI account manager to request a Custom Database Call Data Push configuration and to exchange authentication details and payload requirements.
Open a Brilo AI implementation ticket with sample payload requirements and a staging webhook for testing.
Schedule a technical implementation call with your Brilo AI engineering contact to validate schema, retries, and redaction rules before production rollout.