Join CRM Contacts
Merge contact lists with different email domains, name variations, and typos, when the primary keys come from different systems.
$4.90 • 99.9% accuracy • 1,000+ contacts
EveryRow Matcher
Find matching rows
A matcher figures out which rows belong together, even when names, IDs, and spellings differ. Join tables or deduplicate without matching keys.
▶ 2-min demo video coming soon
Give your AI a team of matchers
Claude Code / AI Agents
claude plugin marketplace add futuresearch/everyrow-sdk claude plugin install everyrow@futuresearch Then ask: "Merge contacts.csv with companies.csv matching contact company to company name"
Python SDK
pip install everyrow
from everyrow import merge
result = merge(
left=contacts,
right=companies,
criteria="Match contact's
company to company name"
)Pricing
Start with $20 in free credits. No credit card required. Pay only for what you use—costs scale with match complexity.
| Task | Rows | Cost/row | Accuracy |
|---|---|---|---|
| Company → Ticker | 438 | 0.23¢ | 100% |
| Contact matching | 1,176 | 0.42¢ | 99.9% |
| Product → Vendor | 1,996 | 0.45¢ | 91.1% |
| CEO → Company | 438 | 0.86¢ | 98.2% |
Why costs vary
everyrow uses a cascade strategy: exact match → fuzzy match → LLM → web search. Simple matches (exact strings) are nearly free. Complex matches (Photoshop → Adobe) require LLM reasoning. Ambiguous matches may trigger web research. You only pay for the intelligence each row needs.