Agents

Deep Research

Deep Research is for questions that outlive a chat turn. It proposes a plan and waits for your approval, sends parallel researchers after each sub-question, checks every claim against the passage it rests on, and comes back with a cited report you can export into a workspace.

At a glance

Handle@deep-research
AvailabilityEnabled on demand under Build โ†’ Capabilities
Where you use itThe Research page in the main menu, or chat (the Orchestrator can hand it a whole research goal)
Tagsbackground
Model tieradvanced
Autonomytrusted โ€” the only built-in above supervised: it may write without pausing, but a destructive call still parks
Toolsweb_search, web_fetch, search_knowledge, code_execution, generate_document, generate_image
Skillsresearch-method, source-triage, contradictions, report-writing, and three playbooks
SchedulableYes โ€” a weekly brief is an automation
Two engines, one switch Deep Research has a research engine โ€” the plan-approve-research-verify flow this page describes โ€” and the original single-agent background run. An org admin chooses per organisation under Admin โ†’ Governance โ†’ Research โ†’ Use the new research engine. With it off, the Research page says so before anyone types, and Deep Research runs as described under The classic run. An organisation that has published its own Deep Research definition keeps it either way.

Asking a question

The Research page: a question box, Sources (Web + internal, Web only, Internal only), Depth (Quick, Standard, Exhaustive โ€” 3โ€“6 sub-questions), a Playbook picker, the Workspace set to My Personal workspace (default), a Start research button, and a list of earlier research with status badges.
The Research page. Nothing is searched until you approve the plan and its estimated cost.
SourcesWeb + internal, Web only, or Internal only (your organisation's knowledge, under your own access)
DepthQuick โ€” up to 3 sub-questions, a broad survey ยท Standard โ€” 3โ€“6 sub-questions ยท Exhaustive โ€” 5โ€“8 sub-questions, read closely
PlaybookOptional method for a familiar shape of question: market sizing (triangulate top-down and bottom-up), literature review (surveys first, studies weighed by design), vendor comparison (one fixed criteria matrix)
WorkspaceWhere the research, its evidence and its report live. Defaults to your Personal workspace โ€” it is never picked silently

Your research below the form lists every run with its date, researchers finished, cost and status.

How a run proceeds

The run view shows the phases as a strip โ€” Scope ยท Plan ยท Research ยท Consolidate ยท Write & verify ยท Deliver โ€” with budget meters for cost, searches, tokens and time underneath.

  1. Scope

    If the question is ambiguous, it asks you a few short questions in a form (a date range, a region, what "large" means). If nobody is there to answer, it states the assumptions it made instead.
  2. Plan โ€” and you approve it

    You see the sub-questions it will research, each with what an answer must contain, plus the estimated cost, searches and time. Approve, edit the sub-questions, or cancel โ€” right in the chat or on the run page. If the estimate is over what your organisation lets you approve alone, an administrator approves the spend from their inbox.
  3. Research, in parallel

    Each sub-question gets its own researcher. Researchers search broad then narrow, prefer primary sources, and record notes โ€” each a claim tied to the exact passage it came from. A note whose passage is not in the source it cites is refused.
  4. Consolidate, then follow up once

    Findings are merged and gaps or contradictions identified; up to one round of follow-up questions (marked f1, f2โ€ฆ) goes back out to researchers.
  5. Write & verify

    The report is written only from the recorded notes. Every sentence is then checked against its passage: an unsupported sentence is removed, a partly supported one is rewritten or hedged, and the original success criteria are re-checked on the final text.
  6. Deliver

    The report arrives with its Evidence and Verification sections and a computed confidence for each finding.

Watching the researchers

A finished research run on India's EV car market: the phase strip from Scope to Deliver all complete, budget meters for cost, searches (107/150), tokens and time (8/60 min), a list of researchers q1โ€“q4 and follow-up f2 with their searches, sources and notes, and one researcher opened to show its activity (load_skill, web_search, web_fetch calls) and its notes with confidence and verdict badges.
A run's page. Each researcher shows its searches, sources, notes and cost; open one to see its tool activity and the notes it recorded, each badged with confidence and verdict.

The report tabs are Report, Evidence (every note and the passage behind it), Sources, Verification (what the checker removed or rewrote, and why), and Plan & trace.

Confidence is computed, not claimed

Taking the report with you

Export to Word, PowerPoint or Markdown into any workspace's Documents, with numbered references, or Open in editor to keep working on it with the Document Author. Citations in the report render as [src:N] pills that open the source.

Internal sources stay internal A report can rest on your organisation's documents. Anyone viewing it who cannot open one of those documents sees it as "Internal source" and does not see the findings drawn from it. Exporting a report that uses internal evidence into a different workspace asks you to confirm first. Research runs also screen fetched pages for prompt injection and apply outbound DLP once anything internal has been read.

Administration

Under Admin โ†’ Governance โ†’ Research an org admin sets:

An eval pack for the engine can be installed from Build โ†’ Capabilities; its planner and verifier cases run without invoking any researcher.

The classic run

With the research engine off, Deep Research runs as a single background run: it writes research-plan.json first, works the steps with a checkpoint after each (a worker that dies resumes from the last one), reports progress to your inbox, accepts steering at the next step boundary, and synthesizes a cited answer โ€” marked budget-limited if it hits its one-hour wall clock rather than truncating.

When the router picks it "Research X and produce a document" is this agent's whole job, so the classifier may hand it the entire goal in one hop rather than splitting a research brief across several agents. The user's goal travels with the delegation, so it never has to ask what the topic was. See the Orchestrator.
It is a normal agent, so you can change it Every built-in is an ordinary org-ring registry agent with a versioned Agent.md. Edit it, publish a new version, roll back โ€” the platform only re-publishes its own definition when you have not taken it over. See Build & promote.