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Monitor events can feed directly into a Task API call to go deeper on any detected signal. Use follow-up tasks to enrich a signal with structured fields or launch a full research report—without any manual handoff. The flow is the same in both cases: receive a webhook, fetch the event, pass its output.content as the input and its event_id as previous_interaction_id to a new Task Run. Passing event_id as previous_interaction_id carries the monitor event’s full context forward into the Task run, preserving provenance through every step of the chain. See Interactions for details.

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Scenario 1: Structured Enrichment on a Detected Event

Use this when you want to extract machine-readable fields from a detected event—for example, pulling company, amount, and round from a funding announcement.
cURL
# 1. Fetch the event
EVENT=$(curl --silent \
  --url "https://api.parallel.ai/v1/monitors/${MONITOR_ID}/events?event_group_id=${EVENT_GROUP_ID}" \
  --header "x-api-key: $PARALLEL_API_KEY")

OUTPUT=$(echo $EVENT | jq -r '.events[0].output.content')
EVENT_ID=$(echo $EVENT | jq -r '.events[0].event_id')

# 2. Enrich with structured extraction
curl --request POST \
  --url https://api.parallel.ai/v1/tasks/runs \
  --header 'Content-Type: application/json' \
  --header "x-api-key: $PARALLEL_API_KEY" \
  --data @- <<EOF
{
  "input": "$OUTPUT",
  "processor": "base",
  "previous_interaction_id": "$EVENT_ID",
  "output_schema": {
    "type": "json",
    "json_schema": {
      "type": "object",
      "properties": {
        "company": { "type": "string", "description": "Company that raised funding" },
        "amount_usd_millions": { "type": "number", "description": "Amount raised in USD millions" },
        "round": { "type": "string", "description": "Funding round, e.g. Series A" },
        "lead_investor": { "type": "string", "description": "Lead investor name" }
      }
    }
  }
}
EOF
See Task Enrichment for full details on structured extraction, output schemas, and polling.

​
Scenario 2: Deep Research on a Detected Event

Use this when you want a comprehensive report on a detected signal—for example, analyzing the strategic implications of a regulatory ruling or a competitor announcement.
cURL
# 1. Fetch the event
EVENT=$(curl --silent \
  --url "https://api.parallel.ai/v1/monitors/${MONITOR_ID}/events?event_group_id=${EVENT_GROUP_ID}" \
  --header "x-api-key: $PARALLEL_API_KEY")

OUTPUT=$(echo $EVENT | jq -r '.events[0].output.content')
EVENT_ID=$(echo $EVENT | jq -r '.events[0].event_id')

# 2. Launch deep research
curl --request POST \
  --url https://api.parallel.ai/v1/tasks/runs \
  --header 'Content-Type: application/json' \
  --header "x-api-key: $PARALLEL_API_KEY" \
  --data @- <<EOF
{
  "input": "Research the following event in depth and summarize its strategic implications: $OUTPUT",
  "processor": "ultra",
  "previous_interaction_id": "$EVENT_ID"
}
EOF
Deep research runs are asynchronous. Poll GET /v1/tasks/runs/{run_id} or use a Task webhook to receive the completed report. See Deep Research for full details.
  • Interactions: How previous_interaction_id chains context across API calls.
  • Task Enrichment: Structured data extraction at scale.
  • Deep Research: Multi-step research reports from natural language prompts.
  • Research Basis: Citations and reasoning on Task API outputs.
  • Events: Event model and retrieval options.