FoundryOne™
Our B2B-tuned entity-resolution engine powering Google Sheets, Gremlin CLI, and the FoundryOps API. Built for 10M+ rows with graph-powered context from Foundry Graph — even partial or incomplete data gets matched accurately.
When matching IBM vs International Business Machines vs ibm.com, FoundryOne returns all three with explainable reason chips showing domain match + parent company signal + alias match.
Core Capabilities
Performance at scale
Cloud-native architecture, 10M+ rows, smart blocking for speed and recall.
→ 10M-row dedupes in minutes, not hours
Explainable accuracy
Reason chips, domain & family signals, and transparent scoring.
→ Audit every match for compliance
Graph-enhanced matching
Missing company name? Only have a domain? We backfill from Foundry Graph automatically.
→ Partial data still gets matched accurately
Why Multi-Algorithm Matching Matters
Unlike tools that rely on a single matching technique (usually fuzzy string matching), FoundryOne combines multiple specialized algorithms and picks the right one for each data type. Here's why that matters:
"IBM Corp""International Business Machines"→ Don't waste hours manually merging obvious duplicates
"Saelsforce Inc"→ Dirty data doesn't break your CRM hygiene
"Société Générale""Societe Generale"→ Global companies with non-English names work correctly
"GE Healthcare""General Electric Company"→ Attribution shows the real parent company
"Apple Inc""apple.com"→ Web traffic and CRM data unified automatically
Every match includes reason chips showing exactly which algorithms fired, so you know why FoundryOne made each decision.
No black boxes. No guesswork.
| Scenario | Single-Algo Tool | FoundryOne Multi-Algo | Why It Matters |
|---|---|---|---|
| "IBM Corp" vs "International Business Machines" | ❌ Low similarity (30%) | ✅ Token acronym match (95%) | RevOps teams don't waste hours manually merging obvious matches |
| "Saelsforce" (typo) vs "Salesforce" | ❌ Treated as different | ✅ Levenshtein + phonetic | Dirty data doesn't break your CRM hygiene |
| "Société Générale" vs "Societe Generale" | ⚠️ Accent mismatch | ✅ Unicode normalization | Global companies with non-English names work correctly |
| "GE Healthcare" vs "General Electric" | ❌ Different entities | ✅ Parent-child hierarchy | Attribution reports show the real parent company |
| "apple.com" vs "Apple Inc" | ❌ No overlap | ✅ Domain → company lookup | Web traffic and CRM data can be unified |
Engine + Graph: Better Together
FoundryOne doesn't just match what you give it — it applies graph intelligence first to maximize accuracy.
You provide
Partial records — maybe just a domain, or a company name with typos, or leads from a tradeshow.
Graph backfills
We look up domains, normalize names, add parent companies, and fill in LEI/QID identifiers automatically.
Engine matches
Now with complete data, multi-algorithm matching finds the right accounts with high confidence.
The result: matches that would fail with incomplete data now succeed — with full audit trails.