Inside FoundryOps: FoundryOne™ & the Foundry Graph™
The accuracy you see isn't magic—it's engineering. A high-performance entity-resolution engine + a living open-data graph deliver explainable, privacy-safe precision across every FoundryOps product.
What is FoundryOne™?
FoundryOne is our B2B-tuned entity-resolution engine powering Google Sheets, Gremlin CLI, and the FoundryOps API. Built for 10M+ rows, multi-core performance, and zero-guesswork matching with reason chips.
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.
Performance at scale
Multi-core, 10M+ rows, smart blocking for speed and recall.
→ Run 10M-row dedupes locally without cloud costs
Explainable accuracy
Reason chips, domain & family signals, and transparent scoring.
→ Audit every match for compliance
Privacy-safe architecture
Open data sources, no PII resale, in-memory processing.
→ No vendor lock-in to data brokers
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 |
What is the Foundry Graph™?
A continuously updated, privacy-safe corporate graph from public sources (Wikidata, official registries), mapping domains, brands, and hierarchies. Updated nightly with full audit trails—every data point is traceable to its source. No PII, no resale, no black boxes.
Why Transparency Matters
Unlike opaque data brokers who won't tell you where their data comes from, every attribute in the Foundry Graph is traceable to Wikidata or official registries. Full audit trails, privacy-safe first-party crawls, and nightly automated updates—no black boxes, no mystery data.
What This Means for Your Matching
- →Better multi-branch matching: 290K+ parent/subsidiary links mean FoundryOne can collapse subsidiaries into a single enterprise record for ABM rollups
- →Domain family intelligence: 69K+ domain mappings significantly improve domain-based matching accuracy
- →Regional expansion: Strongest coverage in US/EU with rapid APAC growth—230 countries represented
How they work together
Built for a Global Audience
Most fuzzy matching tools break when you throw Chinese, Japanese, or Arabic text at them. FoundryOne was engineered from day one to handle the complexity of international data—without corruption, data loss, or character mangling.
Match and deduplicate data in 50+ languages including Chinese (中文), Japanese (日本語), Korean (한국어), Arabic (العربية), Cyrillic (Русский), Hebrew, Thai, and all Latin scripts.
No character restrictions—works with emoji, special characters, and mixed scripts.
FoundryOne automatically detects language script and switches to optimized algorithms. CJK_DICE2 for character-based languages, phonetic matching for Latin alphabets.
Most tools use Levenshtein/Jaro-Winkler designed for alphabetic languages—they fail on CJK.
Full support for IDN (Internationalized Domain Names) and Punycode. Match Russian .рф domains, Chinese .中国 extensions, and all Unicode TLDs.
Script-aware normalization preserves non-Latin characters.
All formulas (FMATCH, FDEDUPE, FENRICH) work with international characters. UTF-8 throughout—reading and writing preserves Unicode integrity.
API communication maintains character integrity across all operations.
Full Unicode preservation in push/pull operations. SOQL queries handle international characters correctly. Multi-encoding CSV import support.
Tries UTF-8, Latin-1, Windows-1252 to ensure your data imports cleanly.
The Foundry Graph represents companies from 230 countries with multi-language labels via Wikidata. Strongest coverage in US/EU, rapid expansion in APAC.
Over a third of profiles include country tags for regional filtering.
Real-World Examples
阿里巴巴集团↔Alibaba GroupCJK_DICE2 algorithm matches character bigrams, no data loss
ソニー株式会社↔sony.jpDomain extraction + graph lookup unifies Japanese/English variants
شركة أرامكو السعودية→✓ MatchedRight-to-left scripts preserved, no character corruption
ПАО Газпром↔gazprom.ruCyrillic-to-Latin domain mapping via Foundry Graph
✅ Complete Unicode Preservation
Full Unicode support across match, dedupe, transforms, and Salesforce sync — no caveats, no character corruption. We've engineered every transform to preserve international characters end-to-end.
"Société Générale" → "societe generale""株式会社メルカリ" → "メルカリ""腾讯控股有限公司" → "腾讯""ООО \"Рога и копыта\"" → "рога и копыта"Note on classification: Title/industry/job function detection uses English keyword matching—it won't corrupt foreign strings, but won't infer non-English semantics. Our UI is currently English-only, but the core engine processes data in any language.
Why This Matters vs. Competitors
- ❌Use Levenshtein/Jaro-Winkler (designed for alphabetic languages)
- ❌Fail on CJK character-based languages
- ❌Strip non-ASCII characters "for safety"
- ❌No script detection or algorithm switching
- ✓CJK_DICE2 algorithm for character-based languages
- ✓Script detection + automatic algorithm switching
- ✓Full Unicode preservation in matching pipeline
- ✓Multi-language Wikidata labels in Foundry Graph
Benchmarks & Proof
Privacy & Trust
Open-data sourcing
Transparent provenance from public datasets like Wikidata
No PII resale
No data brokerage, no selling your customer data
In-memory processing
Regional controls and secure processing
Auditability
Explainability for every match with reason chips
Experience FoundryOne™ Today
Start using FoundryOne-powered matching in Google Sheets, or explore the Gremlin CLI and API.