Measurement tells you that you are missing from the answers. The AI agent — an AI marketer working on your own data — researches the sources behind them, writes the article or the outreach email, and puts the result where your team works.
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You describe the task in plain language. The agent plans it as steps, works through them, and shows what it did at each one — with the data it used, not a summary you have to believe. Content briefs, article drafts, page rewrites, outreach emails and competitor analyses all start from the same measurements.
What you get: Work that takes an analyst a day — pulling the numbers, reading the sources, drafting the brief — comes back in minutes, built on your own data rather than a generic prompt.

Actions and recommendations sit in a to-do table until you run them, each with the effort it costs. The agent cannot change your data or send anything at all: it runs read-only, because a tool that could approve its own writes would not be a safeguard.
What you get: You can hand the agent real work without handing over control — nothing goes out under your name until a person approves it.

Every session exports as PDF or Word. The agent itself has read-only access to your workspace, on purpose: it writes drafts, and what happens to them is your call. Texts can go on into Content Studio (beta), the content optimizer that scores them for AI readiness before you publish.
What you get: Drafts arrive in a form your team, your client or your editor can use straight away — no reformatting, no copying between tools.
Going deeper: The agent in the documentation.
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