EveryRow Matcher

Find matching rows

A matcher identifies which rows refer to the same entity, catching abbreviations and name variations that string matching misses.

Try it Give to your AI

▶ 2-min demo video coming soon

Diagram showing 500 CRM records deduplicated to 124 unique entities: AbbVie Inc variants merged, ASML variants merged

0.1-0.35¢per row

98% accuracyvs 82% fuzzy matching

Screenshot showing CRM records with duplicate company entries identified

Clean Company Datasets

Easily find duplicate vendors, customers, or investments when names change.

$1.67 for 500 rows • 76% duplicates

Case study →Try it →

Screenshot showing researcher names with career changes matched as same person

CRM Deduplication

Match people who changed jobs, emails, or names, where no row exactly matches.

$0.42 for 200 rows • 98% accuracy

Case study →Try it →

🧠

Clean Datasets

Dedupe ML Training Data

Remove semantic duplicates, even when not similar by fuzzy strings or embeddings.

$4.21 for 3,000 rows • 5.3 min

Tutorial →Try it →

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:
"Dedupe contacts.csv
 treating entries as
 duplicates if they're
 the same person"

Agent setup guide →

Python SDK

pip install everyrow

from everyrow.ops import dedupe
result = await dedupe(
  input=crm_data,
  equivalence_relation=
    "Same legal entity"
)

Get API key →Docs →

Pricing

Start with $20 in free credits. No credit card required. Costs scale with the number of rows—deduplication compares every row pair intelligently.

Rows	Time	Cost
200	~90 sec	~$0.40
500	~2 min	~$1.67
2,000	~8 min	~$7

10 minute workflow: import, dedupe, export

everyrow.io/dedupe will not only clean your data, it will also identify which rows were duplicates, and show you which one is canonical and has the right other fields.