The tradecraft built the data.
The data shaped the tradecraft.
Most data companies follow a predictable playbook: aggregate records from third parties, clean them up, and sell access. The data sits in one silo. The expertise – if it exists – sits in another. When AI enters the picture, it gets bolted on through prompts and context windows that degrade with scale.
Sayari took a fundamentally different path. Over the past decade, three assets grew together – and that co-development is the moat.
10.6B+ longitudinal corporate and trade records from non-indexed, often ephemeral sources – including records removed by adversaries that are now exclusively preserved in Sayari’s archive. Full global coverage including China, Russia, offshore jurisdictions, and emerging economies. Every data point traceable to its source document.
650K+ lines of entity resolution code. 67K+ analyst-labeled decisions. 1K+ analytical reports. 300+ hours of recorded analyst walkthroughs. 565 proprietary parsers. This is a record of not just what experts concluded, but why – over more than a decade of real-world economic security analysis.
Domain-specific benchmarks that define what rigorous reasoning looks like for economic security – not just correct answers, but correct reasoning. A benchmark for identifying state-linked structures tests whether the model can distinguish a firm operating normally from one serving as a procurement vehicle based on signals designed to obscure exactly that.
“The commercial world model and the tradecraft produced each other: the expertise was honed on this specific data, and this data was shaped by the expertise. Neither can be acquired independently because they grew together over a decade.”
What makes Sayari’s data foundation irreplicable.
Sayari is the only corporate intelligence data provider that exclusively collects from official, public government sources – and provides the original source documents as evidence. We maintain 565 proprietary source-specific parsers that extract structured data from corporate registries, commercial gazettes, tax authorities, litigation databases, and customs agencies – including unstructured content from higher-risk countries that legacy providers don’t cover.
The U.S. Army TACOM displaced a competitor specifically because that competitor could not provide original source documentation for leadership briefings. Sayari’s glass-box approach was the deciding factor.
A multi-stage, conservative-by-design pipeline that connects records across jurisdictions, languages, and identifier systems into unified entity profiles. Domain expertise is embedded in the resolution rules, not bolted on afterward – written by analysts who understand why a “control party” means something different in Luxembourg than in Hong Kong.
AI-powered entity resolution rolling out in 2026 – reinforcement learning to resolve the sparsest and messiest datasets against our high-quality master data.
4B+ trade transactions – bills of lading, customs declarations, cargo manifests from 85+ authoritative trade data sources across 75+ reporting countries – integrated into the same entity graph as corporate ownership. A sanctioned entity’s trade counterparties surface automatically alongside its ownership chain, revealing exposure that appears clean in either data source alone.
Proprietary bills of materials that break finished goods into constituent components mapped to HS codes – delivering a product-specific supply chain picture that filters irrelevant trade relationships. Unlike competitors offering “predictive” supply chains, every relationship traces to actual customs data.
Microsoft’s Cloud Supply Chain team chose Sayari over Altana in a head-to-head evaluation for UFLPA compliance, internally describing Sayari as “evidence-based” – protecting an $85B data center construction program.
Sanctions evaders, weapons proliferators, and state-linked actors don’t operate through well-documented Western European registries. They operate through offshore financial centers, opaque jurisdictions, and permissive markets – exactly where legacy data providers have the thinnest coverage.
Machine translation across 14 languages. Transliteration support for 13 non-Latin scripts. A 2024 Fortune 500 POC found 3.4× more beneficial ownership relationships with Sayari versus direct registry lookups.
The critical differentiator is not that Sayari has data – it’s that Sayari’s data is pre-connected into a single traversable knowledge graph. Competitors who have volume often have disconnected data, or data that can only be connected manually by analysts at a much smaller scale.
From raw government records to actionable intelligence.
700+ authoritative government sources. 565 proprietary parsers extract structured data from unstructured documents in original language – not scraped, not rented, not self-attested.
Multi-stage entity resolution connects records across jurisdictions, languages, and identifier systems. Domain expertise embedded in the rules, not bolted on afterward. 10.6B+ records → 500M+ companies + 600M+ individuals.
Machine translation across 14 languages. Transliteration for 13 non-Latin scripts. Address geocoding (80% of 900M+ addresses). Risk signal computation across sanctions, PEPs, adverse media, and network propagation.
3B+ pre-computed relationships link entities across ownership, trade, directorship, and control structures. Beneficial ownership chains traced to 10+ degrees. Product-specific supply chains mapped to Tier 5+.
Biweekly full graph rebuilds. Nightly watchlist builds. OFAC, EU, UN, and OFSI sanctions updates within 4 hours of publication. Every build includes new sources, re-computed entity resolution, and improved enrichment.
Glass box, not black box.
Every data point in the knowledge graph traces to its underlying primary source document. Every relationship cites the registry filing, customs record, sanctions listing, or regulatory disclosure that establishes the connection. Every supply chain in Sayari Map is powered by real, historical shipment records – not AI-generated predictions.
| Sayari | Legacy Providers |
|---|---|
| ✓ Primary-source government registries | Self-attested or third-party-sourced data |
| ✓ Original source documents per record | Data provenance obscured or unavailable |
| ✓ Deterministic resolution on hard identifiers | Probabilistic matching with confidence scores |
| ✓ Trade-data supply chains from real customs records | Inferred or survey-based “predictive” supply chains |
| ✓ Audit-grade evidence chain, exportable per alert | Alert-only output, no evidence chain |
Three reasons the data foundation can’t be assembled from parts.
Sayari’s archive includes records from non-indexed and ephemeral sources – corporate filings, trade documents, and ownership records that adversaries have since removed from public access. This data is exclusively preserved in Sayari’s world model. Web scraping captures current state – not the historical record that reveals how adversarial networks were built.
650K+ lines of entity resolution code. 67K+ analyst-labeled decisions. 565 proprietary parsers. 1K+ investigative reports. This took a decade of real-world economic security work to produce. It can’t be loaded into a prompt, purchased from a vendor, or replicated by a model trained on general internet data. Research shows model performance degrades 14-85% as context length grows, even with perfect retrieval.
Businesses that never had to learn to refine messy real-world data – by instead licensing clean content from elsewhere – never developed expertise in the messiness that defines the real world. Sayari’s entity resolution rules were written by analysts who understand the data. The parsers by engineers who know which fields matter for which missions. These assets compound. The moat widens every quarter.
Data quality measured by outcomes, not volume.
Alert volume reduction at a top-10 global bank after deploying Sayari entity resolution pre-screening.
More true-positive beneficial ownership relationships vs direct name matching, Fortune 500 POC against 10,000 entities.
Of Sayari-detected risk absent from global watchlists – hidden within nested ownership, trade, and undisclosed relationships.
Of global supply chains mapped to 4+ supplier tiers automatically.
Median response time for full entity resolution including ownership traversal.
Three ways to put the data foundation to work.
Traverse ownership chains, map N-tier supplier networks with product blueprints, and export evidence packages with source citations per relationship.
API-native entity resolution and continuous monitoring. Batch screening, webhook-based monitoring, and ERP integration (SAP GTS and others).
Global data file via S3 (CSV, Parquet, or JSON). Entity and relationship files with indexed attributes. Quarterly refreshes with schema mapping support.
Bring a real entity. We’ll show you what the world model finds.
The most useful evaluation is running the Commercial World Model against an entity from your actual universe – a counterparty you’re uncertain about, a supplier you need to trace upstream, or a target you’ve already spent time on.