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Overview

Deep Research takes a free-text brief about one research target — a company, a person, or a team — and produces a cited report. A reasoning agent plans the research, fans out research agents that gather evidence from the web and Extruct’s data sources, reviews what came back, and synthesizes the result. It is implemented through the deep_research_tasks endpoints in API Reference.

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This Path Works Best When

  • You want a deep, sourced report on one target: account planning, buyer research, initiative summaries, diligence.
  • You are researching a person before outreach or a meeting: who they are, what their team owns, and the best angle to open a conversation.
  • You need every claim backed by citations, or structured output that downstream systems can parse.
  • You are willing to wait minutes for an asynchronous task in exchange for depth.

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Choose Another Path If

  • You want to discover many companies matching criteria. Use Deep Search.
  • You want repeatable enrichment across a list of companies. Use AI Tables.
  • You need one company’s profile facts instantly. Use Company Lookup.

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Prerequisites

Deep Research requires a Pro plan, and starting a task requires the full depth budget in available credits (see Costs below). 
export EXTRUCT_API_TOKEN="YOUR_API_TOKEN"
Generate tokens in Dashboard API Tokens. For full setup, see Authentication.

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Endpoints used

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Workflow

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1) Create a task

Write the brief like a request to a research analyst: a detailed paragraph naming the target, your own context (what you sell or research, who your buyer is), and the decision the report should support. Detailed, specific briefs reliably produce better reports than one-liners — “Help me break into Shell” is a bad brief; the example below is a good one. 
TASK_RESPONSE=$(curl -sS -X POST "https://api.extruct.ai/v1/deep_research_tasks" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer ${EXTRUCT_API_TOKEN}" \
  -d '{
    "brief": "We sell a cloud cost-optimization platform to large enterprises; typical buyers are VPs of Infrastructure and FinOps leads. I am preparing outreach to Shell. Research how Shell'"'"'s IT and digital organization is structured, who owns cloud infrastructure and FinOps decisions, which cloud, data, or efficiency initiatives they announced in the last 18 months, and which vendors or system integrators they already work with. I want practical conversation angles tied to live initiatives, plus any signals of cost-cutting programs or budget pressure.",
    "depth": "medium"
  }')

TASK_ID=$(echo "${TASK_RESPONSE}" | jq -r '.id')
echo "${TASK_ID}"
Requires jq. If unavailable, copy id manually from the response. People are first-class targets too — include your own context and the profile to research: 
curl -sS -X POST "https://api.extruct.ai/v1/deep_research_tasks" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer ${EXTRUCT_API_TOKEN}" \
  -d '{
    "brief": "Here is my company: example.com. We sell AI-powered sales-enablement software to mid-market B2B teams. Research this person and the team they work with: https://www.linkedin.com/in/example-profile. I want their role and scope, what their team owns, recent initiatives or public statements, tools they already use, and the best angle to open a conversation.",
    "depth": "medium"
  }'

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2) Poll until done

curl --get "https://api.extruct.ai/v1/deep_research_tasks/${TASK_ID}" \
  -H "Authorization: Bearer ${EXTRUCT_API_TOKEN}"
Poll every 10–15 seconds. While running, the counters show progress: iterations (analysis steps), agents (research agents completed), sources (unique sources collected). The task is finished when status is done or failed.

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3) Read the report

For a markdown task, report.kind is "markdown": the markdown cites sources with bracketed ids like [1] that resolve against report.sources (id → URL). 
curl -sS --get "https://api.extruct.ai/v1/deep_research_tasks/${TASK_ID}" \
  -H "Authorization: Bearer ${EXTRUCT_API_TOKEN}" | jq -r '.report.markdown'
Always check report.degradation_reasons. It lists, in plain language, anything that reduced coverage — research stopped at its budget or step limit, or some research agents failed. Empty for a clean run. Show these notes to your users alongside the report. If status is failed, read failure_reason: a rejected brief includes suggestions for fixing it, and failed tasks refund all their charges.

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Structured reports (schema mode)

Pass an output_schema to get machine-readable output instead of markdown. The schema must be a JSON Schema object ("type": "object"); it is validated in full at creation time. 
curl -sS -X POST "https://api.extruct.ai/v1/deep_research_tasks" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer ${EXTRUCT_API_TOKEN}" \
  -d '{
    "brief": "We provide fraud-prevention APIs for fintech platforms and are building an account plan for Stripe. Summarize Stripe'"'"'s enterprise product initiatives from the last 12 months, identify concrete product or partnership angles where a fraud-prevention vendor could plug in, and flag risks that could stall a deal.",
    "depth": "high",
    "output_schema": {
      "type": "object",
      "properties": {
        "summary": {"type": "string"},
        "recommended_angles": {"type": "array", "items": {"type": "string"}},
        "risks": {"type": "array", "items": {"type": "string"}}
      },
      "required": ["summary", "recommended_angles", "risks"]
    }
  }'
When done, report.kind is "schema":
  • report.fields — values conforming to your schema. A done schema report is guaranteed to validate against it.
  • report.basis — for every field, the ids of the sources supporting that value (empty when a value is unsupported — treat those with care).
  • report.sources — the id → URL registry the basis ids resolve against.
Design tip: keep schemas focused (a handful of fields per task). Each field should name one decision-relevant fact or list; the per-field basis is your audit trail.

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Costs

  • depth sets the research-agent budget: medium = 25, high = 50, xhigh = 75.
  • Starting a task requires the full budget in available credits, but you are billed only for agents that actually run (1 credit each). A focused brief often finishes well under budget.
  • Failed tasks — rejected briefs, mid-run credit exhaustion, internal errors — refund all their charges.