LLM Path

Overview

The LLM path is the fastest way to send a voice notification. You provide a message string and Echo generates a contextual call script on the fly using your business context (business_name, business_summary, industry) and the message you provide. No agent definition required. No variables. Just a customer ID and a message.

Sending an LLM-path Notification

curl -X POST https://api.meetecho.ai/v1/notifications \
  -H "x-api-key: echo_..." \
  -H "Content-Type: application/json" \
  -d '{
    "customer_id": "8cc6199f-9466-46f2-9db7-936f3c2c1c0b",
    "message": "Your premium trial expires in 24 hours. Log in to upgrade and keep your access.",
    "collect_feedback": true,
    "max_duration_seconds": 120
  }'

Response

{
  "notification": {
    "id": "13eea9cc-...",
    "status": "in_progress",
    "message": "Your premium trial expires in 24 hours...",
    "collect_feedback": true,
    "max_duration_seconds": 120,
    "target_phone_e164": "+14155552671"
  },
  "call": {
    "callId": "call-abc123",
    "status": "queued"
  }
}

Request Fields

Field	Type	Required	Description
`customer_id`	UUID	Yes	The customer to call. Must belong to your project.
`message`	string	Yes	The core notification content. Fills `{{message}}` in the generated script.
`context`	string	No	Additional per-call context. Fills `{{context}}` in the generated script.
`collect_feedback`	boolean	No	If `true`, the AI asks the caller to confirm, cancel, or reschedule at the end of the call. Default: `false`.
`max_duration_seconds`	integer	No	Maximum call duration. Range: 30–600. Default: 180.

Using `collect_feedback`

When collect_feedback: true, the generated call script includes a feedback prompt at the end of the conversation. The AI will ask the caller to take an action — confirm, cancel, reschedule, or similar — depending on the message content.

{
  "customer_id": "...",
  "message": "Your appointment with Dr. Patel tomorrow at 10 AM is confirmed.",
  "collect_feedback": true
}

The caller’s response is captured in the webhook payload under call_result.

Using `context`

The context field is for runtime nuance you don’t want hardcoded into the message. Use it to pass background information that shapes how the AI conducts the conversation:

{
  "customer_id": "...",
  "message": "Your subscription payment failed.",
  "context": "Customer has been with us for 3 years. Their card expired last month. Be empathetic.",
  "collect_feedback": true
}

context is invisible to the caller — it’s instructions for the AI, not dialogue. Keep it factual and concise.

Controlling Call Duration

Use max_duration_seconds to cap how long the call can run. This is useful for:

Cost control — billing is per minute, so shorter limits reduce exposure
User experience — preventing runaway conversations on simple notifications
Compliance — some use cases require call length limits

{
  "customer_id": "...",
  "message": "Your order has shipped. Expected delivery: Friday.",
  "max_duration_seconds": 45
}

The call ends automatically once the limit is reached, regardless of conversation state.

What Echo Generates

When you use the LLM path, Echo combines:

Your business_name, business_summary, and industry from signup
The customer’s first_name and last_name
Your message and optional context

…into a contextual call script that the AI uses to conduct the conversation. The script is generated fresh for each call — you won’t see it directly, but it reflects your business identity.

LLM Path vs Agent Path

	LLM path	Agent path
Setup	None	Create an agent first
Prompt control	Echo generates it	You write it
Tone consistency	Variable	Fully consistent
Custom variables	Not available	Full `{{variable}}` system
Structured output	No (`call_result` is null)	Yes, via `output_schema`
`collect_feedback`	Supported	Not applicable
`max_duration_seconds`	Supported	Not applicable
Best for	Quick one-off alerts	Templates, surveys, brand voice

For full control over the conversation, structured output extraction, and consistent brand voice across thousands of calls, use the Agent approach.

Getting Started

Guides

Overview

Sending an LLM-path Notification

Request Fields

Using `collect_feedback`

Using `context`

Controlling Call Duration

What Echo Generates

LLM Path vs Agent Path

​Overview

​Sending an LLM-path Notification

​Request Fields

​Using collect_feedback

​Using context

​Controlling Call Duration

​What Echo Generates

​LLM Path vs Agent Path

Overview

Sending an LLM-path Notification

Request Fields

Using `collect_feedback`

Using `context`

Controlling Call Duration

What Echo Generates

LLM Path vs Agent Path