Map-first intelligence for semiconductor supply chains. Start with the global map, then drill into company, country, facility, and scenario views.
How intelligence outputs are built and validated.
This platform is designed for traceable semiconductor research. Company, facility, country, and scenario views are grounded in structured records with explicit provenance, confidence, and freshness metadata.
1. What we track
Coverage model
We track companies, facilities, countries, production stages, materials, products, investments, logistics routes, chokepoints, and dependencies as linked entities. Aliases, parent-subsidiary relationships, and ownership structures are preserved so naming variance does not fragment the data model.
Sources are first-class records and can support multiple claims or relationships. Every major intelligence surface is intended to be read with source and freshness context, not as standalone narrative text.
2. Confidence scoring
Confidence model
Record confidence is normalized from five weighted factors: extraction confidence (0.30), source reliability tier (0.25), review state (0.20), cross-source agreement (0.15), and freshness (0.10).
Quality flags highlight weak-confidence records, low source coverage, stale evidence, duplicate candidates, and conflicting aliases. Flagged records are surfaced in analyst queues for review before broader publication.
3. Freshness policy
Freshness model
Freshness decays by time band and is shown across entity and operations views. Current scoring bands are: up to 30 days, 90 days, 180 days, 365 days, and older than 365 days. Older records carry higher stale-risk weighting.
Source cadence schedules and refresh queues are used to target stale records first. Enrichment follows a non-destructive policy: new evidence fills gaps and extends provenance without blindly overwriting validated fields.
4. Reading outputs
Scores and scenarios
Scores are presented with weighted components and explanation text. Scenarios distinguish direct from indirect impacts and include confidence context so modeled propagation is visible rather than hidden.
Use this methodology page with each entity’s Source panel for due diligence: the score or impact view should always be evaluated alongside source quality and freshness signals.