> ## Documentation Index
> Fetch the complete documentation index at: https://docs.luly.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Analyze Call with AI

> Analyzes a call of calls based using questions and goals.

### Headers

<ParamField header="authorization" type="string" required={true}>
  Your API key for authentication.
</ParamField>

### Path Parameters

<ParamField path="call_id" type="string" required={true}>
  The unique identifier for the call to be analyzed.
</ParamField>

### Request Body

<ParamField body="goal" type="string" required={true}>
  This is the overall purpose of the call. Provides context for the analysis to guide how the questions/transcripts are interpreted.
</ParamField>

<ParamField body="questions" type="string[][]" required={true}>
  An array of questions to be analyzed for the call.

  Each question should be an array with two elements: the question text and the expected answer type (e.g., “string”, “boolean”).

  Fairly flexible in terms of the expected answer type, and unanswerable questions will default to `null`.

  Examples:

  ```json
      "questions": [
          ["Who answered the call?", "human or voicemail"],
          ["Positive feedback about the product: ", "string"],
          ["Negative feedback about the product: ", "string"],
          ["Customer confirmed they were satisfied", "boolean"]
      ]
  ```
</ParamField>

### Response

<ResponseField name="status" type="string">
  Can be `success` or `error`.
</ResponseField>

<ResponseField name="message" type="string">
  Confirms the request was successful, or provides an error message if the request failed.
</ResponseField>

<ResponseField name="answers" type="array">
  Contains the analyzed answers for the call in an array.
</ResponseField>

<ResponseField name="credits_used" type="number">
  Token-based price for the analysis request.

  As a rough estimate, the base cost is `0.003` credits with an additional `0.0015` credits per call in the call.

  Longer call transcripts and higher numbers of questions can increase the cost, however the cost scales very effectively with calls vs. individual calls.
</ResponseField>

<ResponseExample>
  ```json Response
  {
      "status": "success",
      "message": "Successfully analyzed call",
      "answers": [
          "human",
          "Customer found the product sturdy and reliable",
          "A bit heavy",
          true
      ]
  }

  ```
</ResponseExample>