curl --request POST \
--url https://api-lr.agent.ai/v1/action/company_research_v2_answer_question \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"company_id": "<string>",
"question": "<string>",
"output_variable_name": "question_answer",
"use_live_data": true
}
'{
"status": 123,
"response": {}
}Answer a custom research question about a company using cached data and LLM.
curl --request POST \
--url https://api-lr.agent.ai/v1/action/company_research_v2_answer_question \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"company_id": "<string>",
"question": "<string>",
"output_variable_name": "question_answer",
"use_live_data": true
}
'{
"status": 123,
"response": {}
}Bearer token from your account (https://agent.ai/user/integrations#api)
ID of the company to research.
Your research question (e.g., 'What is their pricing model?').
Variable name for the answer. Access answer with {{question_answer.answer}}.
^[a-zA-Z][a-zA-Z0-9_]*$Include web search for more current information.