Rank Firms
Score 1,000 companies by data fragmentation risk. Research every one of them.
$13 for 1,000 leads • 1.3¢/row
EveryRow Scorer
Research, then score
A scorer researches each row on the web, then scores by what it finds. Rank leads, suppliers, or investments by criteria no formula can evaluate.
▶ 2-min demo video coming soon
Give your AI a team of scorers
Claude Code / AI Agents
claude plugin marketplace add futuresearch/everyrow-sdk claude plugin install everyrow@futuresearch Then ask: "Rank companies.csv by likelihood to need data integration tools"
Python SDK
pip install everyrow
from everyrow.ops import rank
result = await rank(
task="Score by likelihood
to need data tools",
input=leads_df,
field_name="score"
)Pricing
Start with $20 in free credits. No credit card required. Costs vary based on research complexity—simple metrics cost less, web research costs more.
| Case study | Rows | Research | Cost |
|---|---|---|---|
| Research permit times | 75 | Government sites | $4 |
| Score investment firms by fit | 500 | Deep web research | $28 |
| Rank S&P 500 by turnover risk | 500 | Financial research | $21 |
| Score B2B leads by ICP fit | 1,000 | From spreadsheet | $13 |
Why costs vary
everyrow.io/rank runs LLM-powered web research agents on your data. Sometimes it easily finds reliable evidence. But much of the time, the agents need to cross-reference multiple data sources and work out what is credible and timely. We measure this on Deep Research Bench. You only pay for the intelligence each row needs.