POST
/
v1
/
batches
/
{batch_id}
/
analyze
Analyze Batch with AI
curl --request POST \
  --url https://app.luly.ai/api/v1/batches/{batch_id}/analyze \
  --header 'Content-Type: application/json' \
  --header 'authorization: <authorization>' \
  --data '{
  "goal": [
    [
      "<string>"
    ]
  ]
}'
{
  "status": "success",
  "pathway_id": "9d404c1b-6a23-4426-953a-a52c392ff8f1"
}

​
Headers

​
authorization
string
required
Your API key for authentication.

​
Path Parameters

​
batch_id
string
required
The unique identifier for the batch of calls to be analyzed.

​
Request Body

​
goal
string[][]
required
An array of questions to be analyzed for each call in the batch.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:
"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"]
 ];

​
Response

​
status
object
Will be success if the request was successful.
​
message
string
Confirms the request was successful, or provides an error message if the request failed.
​
answers
object
Contains the analyzed answers for each call in the batch.The keys are call_ids from the batch, and the array values are the analysis results for each question in the batch.
​
credits_used
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 batch.Longer call transcripts and higher numbers of questions can increase the cost, however the cost scales very effectively with batches vs. individual calls.
{
  "status": "success",
  "pathway_id": "9d404c1b-6a23-4426-953a-a52c392ff8f1"
}