Direct Answer (TL;DR)

Brilo AI can be configured to connect to your serverless functions by calling a secure webhook endpoint (HTTP request) or REST API when specific call events occur. The Brilo AI voice agent can send JSON payloads, receive structured responses, and use those responses to drive the call flow — for example, to look up account data, validate eligibility, or create a case. Connections to serverless functions require a reachable endpoint, an agreed request/response schema, and authentication that you provide. When configured, Brilo AI can invoke your cloud function as an event trigger and continue the conversation based on the function’s response.

Can Brilo AI call my cloud function? — Yes; Brilo AI can call your serverless function via a secure webhook endpoint and use the response to control the voice agent flow.
Can Brilo AI receive data back from my function? — Yes; the voice agent can consume structured JSON responses and map fields into dialog variables or routing decisions.
Does Brilo AI support authenticated calls to my functions? — Yes; Brilo AI can be configured to include authentication headers or tokens when it calls your webhook endpoint.

Why This Question Comes Up (problem context)

Enterprises ask whether Brilo AI voice agent can connect to serverless functions because many organizations run business logic, data lookups, and specialized verification inside private cloud functions. Buyers in healthcare, banking, and insurance need to know whether Brilo AI can trigger those functions in real time during a call without introducing a fragile integration. They also want clarity on security, latency, and how call routing or compliance workflows will be affected.

How It Works (High-Level)

When configured, the Brilo AI voice agent makes an outbound HTTP request (webhook) to your serverless function at defined points in the call flow, such as after intent detection or when a user provides identifying information. The typical flow is:

Brilo AI sends a POST with a JSON payload containing call context and collected fields.
Your serverless function processes the request and returns a JSON response with decision data or next-step instructions.
Brilo AI maps the response fields into dialog variables and continues the conversation or routes the call.

A webhook endpoint is a publicly reachable URL that the voice agent calls to exchange structured data during a call.

Call variables are named fields the voice agent uses to store and pass data between the agent and your function.

An invocation is the single HTTP request/response exchange between the voice agent and your serverless function.

Guardrails & Boundaries

Brilo AI integrations with serverless functions should be designed with clear limits and fallbacks. Brilo AI will not assume retry semantics or data validation beyond configured checks; you must define timeouts and failure behaviors. Typical guardrails include:

Timeout rules: configure how long Brilo AI waits for a response before taking a fallback action (for example, ask to retry, route to a human).
Authentication requirements: require tokens, mutual TLS, or signed payloads as your policy dictates; do not rely on unauthenticated endpoints.
Input sanitization: Brilo AI sends collected user input; your function should validate and sanitize before making decisions.
Partial-data handling: define how Brilo AI continues when the function returns incomplete data.

A fallback action is the configured behavior the voice agent uses when an integration call fails or returns an unexpected result (for example, prompt the caller again or escalate to a human).

Applied Examples

Healthcare example:

A Brilo AI voice agent checks patient eligibility during an inbound call by calling your serverless verification function with the patient ID. The function returns eligibility status and next-authorization steps; the agent reads the result and either transfers to clinical scheduling or creates a follow-up task for staff.

Banking / Financial services example:

A Brilo AI voice agent calls a serverless fraud-check function during high-risk transactions. The function returns a risk score and recommended action; Brilo AI then either continues the transaction path, requests additional verification, or routes to a fraud specialist.

Insurance example:

During a claims intake, the Brilo AI voice agent invokes a claims-precheck cloud function to validate policy coverage. The function responds with covered services and required documents; the agent informs the caller and initiates document collection or escalates to an adjuster.

Human Handoff & Escalation

Brilo AI voice agent workflows can escalate or hand off based on function responses and configured routing rules. Typical patterns:

Conditional handoff: if the function returns a flag (for example, “requires human review”: true), Brilo AI routes the call to a live agent queue or creates a support ticket and schedules a callback.
Warm transfer: Brilo AI can capture context and pass structured data (call variables) to the receiving agent or CRM so the human agent sees the function’s result.
Retry and queueing: when the serverless function is unavailable, configure Brilo AI to retry, ask the caller to hold, or place them in a callback queue.

Setup Requirements

Provide a reachable webhook endpoint (HTTPS) that accepts JSON POST requests and responds with JSON.
Provide authentication details (API key, bearer token, or other agreed method) that Brilo AI will use in the request headers.
Define the request schema and required fields (for example: caller_id, called_number, intent, collected slots).
Define the response schema Brilo AI should expect (for example: action, dialog_text, route_to).
Test the endpoint with a sandbox caller flow to validate latency and error handling.
Configure timeouts and fallback behaviors in the Brilo AI call flow (for example, on timeout → retry once → present fallback prompt).
Map response fields to Brilo AI call variables and routing rules.

Business Outcomes

Connecting Brilo AI voice agent to serverless functions enables real-time decisioning inside existing business logic, reduces manual lookups, and keeps sensitive business rules in your control. Typical operational benefits include faster automated resolutions, better context for live agents after handoff, and centralized governance of verification logic.

These outcomes depend on reliable endpoints, agreed schemas, and tested failure modes.

FAQs

Can Brilo AI call a private function behind a firewall?

Brilo AI requires the endpoint to be reachable over HTTPS from its managed environment. If your function is private, you must expose a secure proxy or use a supported connectivity pattern approved by your security team.

What authentication methods does Brilo AI support for webhook calls?

Brilo AI can send authentication headers or tokens with each request when configured. Your security team should specify the exact scheme (for example, a bearer token or mutual TLS) and the expected header names.

What happens if my serverless function is slow or times out?

If the function exceeds the configured timeout, Brilo AI will follow the configured fallback action (for example, reprompt the caller, perform a cached lookup, or route to a human). You should test typical latency and set conservative timeouts to avoid poor caller experience.

Can the voice agent pass PCI, PHI, or other sensitive data to my function?

Brilo AI can transmit data you include in the payload, but you must ensure the data handling and endpoint meet your compliance requirements. Do not assume transmission or storage protections are in place without explicit contractual or architectural confirmation.

Next Step

Contact your Brilo AI implementation lead or support to request a webhook integration and discuss authentication and timeout policies.
Prepare a sandbox endpoint and sample request/response schemas to validate with a Brilo AI test flow.
Schedule a configuration session with Brilo AI to map response fields to dialog variables and set fallback behaviors.

Can Brilo AI voice agent connect to serverless functions?