Predict future values with research on every row

Ground predictions in web research. Forecast outcomes, timelines, or signals for entire datasets.

A team of researchers on one question

Dispatch a team of research agents, each on a different angle, then synthesize one answer. Can also generate a list.

One researcher per row

Run a web research agent on every row of a table in parallel. Add columns of data you don't have yet.

Score and rank on every row

Assign qualitative scores to leads, companies, or any list, even when data is fragmented across many sources.

Filter with web research on every row

Screen candidates, companies, or leads against qualitative criteria. Fast and accurate at scale.

Join tables using research to match rows

Match rows across datasets without shared IDs. LLM agents look up each record to find the right join.

Deduplicate with research-backed matching

Remove duplicates even when names, formats, and metadata don't match. Handles messy real-world data.