Direct Answer (TL;DR)
Brilo AI handles API response errors with configurable retry and fallback flows so the Brilo AI voice agent can continue the call without exposing raw failure details to callers. When an external API returns an error or times out, Brilo AI can detect HTTP status codes and malformed JSON, apply a retry policy with backoff, invoke a cached or default response, and escalate to a human agent when required. These behaviors are controlled per workflow so you can choose whether the Brilo AI voice agent retries, degrades gracefully, or routes the call to live support. The result is predictable call handling, clearer caller messaging, and audit-ready logs for post-call review.
How will Brilo AI react to third‑party API failures? — Brilo AI retries according to your workflow rules, falls back to default prompts, and can route to a human if configured.
What happens when the webhook returns bad JSON? — Brilo AI flags the response as an error, optionally retries, and follows your configured fallback or escalation path.
Can Brilo AI avoid exposing error details to patients or customers? — Yes. Brilo AI returns safe, scripted messages rather than raw error text when API response errors occur.
Why This Question Comes Up (problem context)
Enterprises ask about API response errors because voice calls often depend on real‑time data from external systems (CRMs, scheduling APIs, verification services). When those systems fail, callers expect a clear result or human help, and regulated sectors (healthcare, banking, insurance) require controlled messaging and audit trails. Buyers want to know how Brilo AI will behave during partial outages, intermittent errors, or unexpected payloads so they can meet SLAs and compliance needs without jeopardizing caller experience.
How It Works (High-Level)
When a Brilo AI voice agent calls your API or webhook, it evaluates the HTTP response and payload against configured rules. Typical workflow steps are:
Validate the HTTP status code and JSON schema.
Apply a retry policy (with configurable attempts and delay) for transient errors.
Use a preconfigured fallback response or cached data if the API remains unavailable.
Trigger an escalation path to a human agent or queue when specific error thresholds are met.
In Brilo AI, an API response error is any non‑successful or malformed reply from an external integration that the voice agent uses to decide call flow. A retry policy is a workflow setting that defines how many times and how frequently the voice agent will re-request an API before failing over. These behaviors are set per‑flow and can be tuned for latency sensitivity or strictness.
Guardrails & Boundaries
Brilo AI enforces safety and operational boundaries so error handling does not leak sensitive data or create unpredictable behavior:
Do not surface raw API errors to callers; Brilo AI returns scripted, non‑technical prompts when external calls fail.
Limit retries for non‑transient errors (for example, authentication failures) to avoid repeated failed attempts.
Define clear escalation triggers (for example, consecutive 5xx responses) so calls move to human agents promptly.
Avoid making the Brilo AI voice agent perform write actions (like financial transactions) when the primary API is in an error state unless a validated failover is available.
A fallback flow is the configured voice script or cached data the agent uses when the primary API fails. An escalation trigger is the condition (error count, error type, or timeout) that sends a call to human support.
Applied Examples
Healthcare example: A Brilo AI voice agent checks an appointment API to confirm a patient slot. If the API times out, Brilo AI will use a neutral prompt such as “I’m having trouble confirming that appointment right now; would you like me to connect you to a staff member?” and log the error for audit. Configure the workflow to avoid returning clinical details when external systems fail.
Banking example: A Brilo AI voice agent queries a balance endpoint. On a 5xx error, Brilo AI can retry once, then present a secure escalation option: “I can’t access account details at the moment; would you like a callback from a representative?” The agent will not read partial or stale balances unless you explicitly configure a cached‑data fallback.
Insurance example: When a claims‑status API returns malformed JSON, Brilo AI flags the response, activates a defined fallback script to collect claimant contact info, and creates a task in your CRM for follow‑up.
Human Handoff & Escalation
Brilo AI supports multiple handoff patterns:
Immediate transfer: Send the caller to a live agent or queue when an API error meets escalation criteria.
Callback scheduling: Offer to schedule a callback and create a ticket with the error context for follow‑up.
Contextual warm transfer: When routing to a human, Brilo AI can attach the error log, last successful data, and caller transcript to the agent’s interface so the human has context.
Configure escalation conditions (error types, retry exhaustion, caller sentiment) so the Brilo AI voice agent follows predictable human handoff rules.
Setup Requirements
Provide an accessible webhook endpoint (HTTPS) that Brilo AI can call for runtime data.
Share authentication details or API keys required for Brilo AI to authenticate (for example, an API key or OAuth credential).
Supply sample success and error responses (JSON schemas) so Brilo AI can validate payloads and detect malformed responses.
Define retry and timeout preferences (number of attempts, backoff strategy, and per‑call timeout).
Configure fallback scripts and escalation rules in your Brilo AI workflow (what callers hear and when to route to human agents).
Provide your CRM or webhook endpoint for error logging and ticket creation, plus field mappings for audit logs.
Test the flow in a staging environment and review logs to confirm retry behavior and safe caller messaging.
Business Outcomes
Properly configured, Brilo AI’s API error handling reduces avoidable live transfers, protects sensitive information during system faults, and keeps caller experience consistent. Teams gain clearer handoff context, faster resolution for escalations, and reliable logs for incident review—helping support and compliance teams manage outages without increasing caller frustration.
FAQs
Can Brilo AI retry an API call automatically?
Yes. Brilo AI can apply a configurable retry policy with timeouts and backoff for transient errors. You decide the number of retries and delays per workflow.
Will callers see the raw error message from a failed API?
No. Brilo AI returns scripted, non‑technical messages for failures by default. You can customize fallback prompts to match brand and compliance requirements.
How does Brilo AI decide when to escalate to a human?
Escalation is based on workflow triggers you set (for example, consecutive 5xx responses, data validation failure, or caller request). When triggered, Brilo AI can transfer the call or schedule a callback and attach the error context.
What logging and audit data does Brilo AI capture for API errors?
Brilo AI logs HTTP status codes, response timeouts, payload validation failures, retry attempts, and the resulting fallback or escalation actions. These logs support post‑call review and incident investigation.
Can Brilo AI use cached data when an API is down?
Yes. You can configure cached or default responses as a fallback. Use cached data cautiously for regulated data; define TTLs and validation rules to avoid stale or incorrect information.
Next Step
Contact your Brilo AI implementation specialist to define fallback scripts, retry policies, and escalation triggers for regulated workflows (appointments, financial lookups, or claims).