AI processors run a model over every row. They are metered by usage, so run a few rows first to gauge the cost.
- Query AI sends a prompt to a model, built from your columns with
/. It has no web access, so give it everything it needs in the prompt.
- Web Research asks a research question per row and returns a cited answer, the go-to when the answer lives on the internet.
- Run an Agent puts one of your agents to work on each row, arriving with its own instructions, tools, and knowledge.
- Summarize Text condenses a long text column, at the length you choose.
Turns messy text into clean columns. Define the fields you want, each with a name and a type, and the extractor pulls them out of the text into a single object cell, one field per value. Use a field downstream by typing / and drilling into it, or flatten it out with Extract Field From Object. It can also extract every occurrence as a list, for example each person mentioned in a document. Like Query AI, it works only with the text you give it.
Scoring Agent
Scores any text against criteria you write yourself. Add each criterion with a weight, set the score range, and every row gets a score per criterion, the reasoning behind it, and a weighted total. For scoring companies against a rubric your organization has already built in QX, use Score Companies on the Integrations page instead.
Draft An Email
Writes a personalized email per row. You supply the fixed text, and anywhere you want AI-written content you add a curly-brace placeholder, such as {write one sentence on why this company is a fit}. The AI fills the placeholders using your columns and context, and can research the recipient on the web unless you switch that off. The result is text in a cell. To place it in a real mailbox as a draft, feed it into Gmail Draft or Outlook Draft, see Integrations.
These chain well: Web Research gathers the raw findings, AI Data Extractor structures them, Scoring Agent ranks the row, and Draft An Email writes the outreach.
