Altsets reveals the supplier and customerrelationships that shape economic exposureacross companies, sectors, and regions.
For investors and traders branching through suppliers, customers, exposure metrics, and second-order public companies.
For funds and institutions pulling directed edges, subsidiary context, history, and exposure estimates.
{
"date": "2026-05-15",
"data": [
{
"supplier": {
"entityKey": "TAIWAN SEMICONDUCTOR MFG CO LTD",
"symbol": "TSM",
"name": "Taiwan Semiconductor Manufacturing Co Ltd",
"country": "TW"
},
"customer": {
"entityKey": "NVIDIA CORP",
"symbol": "NVDA",
"name": "NVIDIA Corp",
"country": "US"
},
"metrics": {
"relationshipSize": {
"value": 4820000000,
"currency": "USD"
}
}
}
]
}View DocumentationPressure fades in some parts of the network and concentrates in others. Altsets maps the dependency paths that decide where stress gets absorbed, where it travels next, and which connected names are exposed before the move is obvious.
Uncover the chokepoints behind chips: foundries, equipment suppliers, packaging firms, substrates, specialty chemicals, silicon inputs, and the capacity-constrained links that connect them across the globe.
Trace how lithium and rare earth shocks move from upstream producers into the industries that depend heavily on their fabrication.
Follow the shift from oil and gas toward renewables as changing energy economics reshape margins, suppliers, and the companies built around legacy or emerging energy systems.
Find smaller suppliers, regional manufacturers, foreign micro caps, and specialized companies sitting closer to the bottleneck than the obvious US-listed trade.
Relationship signals are scattered across filings, presentations, websites, disclosures, news articles, and other sources. Altsets compiles and resolves entities, estimating their revenue and cost attributions to form an economic dependency network.
Evidence is preserved as it moves from source language into a directed, point-in-time relationship record.
Filings, presentations, websites, disclosures, and other sources contain fragments of supplier, customer, and dependency evidence.
Company names, subsidiaries, tickers, regions, products, and private counterparties are matched into usable entities.
Relationship metrics are estimated when values are not disclosed, with source cross-checks for anonymous customers, suppliers, and partially described counterparties.
Human analysts review extracted relationships for consistency, entity accuracy, source support, and relationship direction before publication.
Supply-chain and relationship data has mostly been treated as an institutional product: gated, expensive, and built for enterprise workflows. Altsets brings dependency intelligence into a self-serve platform so individuals can start exploring companies, sectors, and supply chains without waiting on applications or sales calls.
For exploring Altsets before unlocking the live dependency network.
For investors giving their AI agent access to current quantified supply-chain relationships.
For deeper agent research across the complete historical relationship network.