What Supply-Chain Data Adds Beyond Company Filings
July 29, 2026
Altsets
Research by Altsets Research
Combine company-reported concentration and sourcing disclosures with named, directional relationship data to answer network questions that one-company-at-a-time filings leave unresolved.
Data used:Altsets Supply Chain Intelligence: 90k+ entities, 400k+ relationships, 20+ years of history.
Key findings
- Nvidia publicly discloses major direct-customer concentration while leaving the largest customers unnamed, whereas the supplied relationship network provides named downstream counterparties without falsely identifying the anonymous filing customers.
- Micron warns that some materials and services have limited or sole-source supply, while the supplied relationship data adds directional cost exposure for several known suppliers, including ASML at 11.91% of Micron's cost base.
Supply-chain data can add named counterparties, network connections, and economic ranking when company filings leave dependencies anonymous, isolated, or unquantified. Nvidia's fiscal 2026 annual report provides a clear example.
The company disclosed that one direct customer represented 22% of annual revenue and another represented 14%. The filing did not name either customer. The supplied Altsets network separately contains named downstream Nvidia relationships with Quanta Computer, Samsung Electronics, Amazon, Microsoft, and Super Micro Computer.
That does not identify either anonymous 22% or 14% customer. It does give the investor a named relationship map that the filing does not provide.
Filings are strongest at disclosed accounting facts
A filing can establish:
- reported revenue;
- segment mix;
- customer-concentration thresholds;
- risk factors;
- contractual commitments;
- inventory;
- receivables;
- management assumptions;
- legal and accounting disclosures.
Those facts should remain the authoritative source for the company's own reported financial statements. Supply-chain data should not overwrite them. The useful question is what the filing leaves unresolved.
Nvidia shows the identity gap
Nvidia defines direct customers broadly. They can include distributors, ODMs, OEMs, cloud service providers, AI model makers, and system integrators. Its annual report also distinguishes indirect customers that purchase through direct customers.
That disclosure is economically important. But the largest direct customers remain anonymous. A named relationship graph helps the investor research the commercial neighborhood around Nvidia without falsely claiming that a named graph edge corresponds to Customer A or Customer B. The unnamed-major-customer guide covers that specific identification problem.
Micron shows the magnitude gap on the supplier side
Micron's current risk disclosures say only a limited number of suppliers can meet its standards for some materials and services. Micron also warns that certain inputs can be single-source or sole-source and that qualifying new suppliers can take time. That tells the investor that supplier dependency matters.
The supplied Altsets network adds economic weights to several known upstream relationships. ASML is associated with 11.91% of Micron's cost base, followed by Lam Research at 5.52%, Applied Materials at 3.84%, KLA at 2.84%, and Shin-Etsu Chemical at 1.34%.
The point here is not to rebuild a concentration table. The filing provides the operating-risk warning, while the relationship data gives the investor a way to prioritize which named suppliers deserve investigation first.
The two sources answer different questions
A filing might explain whether a company faces concentration or sourcing risk. Relationship data can help identify which known counterparties appear economically important enough to investigate.
A filing might also disclose how much revenue comes from major anonymous customers, while relationship data identifies named customer relationships in the network. Neither source automatically answers every question. The useful workflow combines them.
Public filings can validate the graph too
The relationship graph should not be treated as isolated truth. Public disclosures can independently confirm commercial relationships. For example, Tesla's 2026 filing directly disclosed revenue from SpaceX purchases of Megapack products.
Apple's historical supplier list names SK hynix as an Apple supplier. Those public sources do not reproduce every Altsets metric. They can still provide independent evidence that a relationship exists. That kind of cross-check is important when using any commercial dataset for investment research.
Supply-chain data can also add direction
A company can be economically important to another company in two different ways. Supplier revenue percentage asks how much the customer matters to the supplier. Customer cost percentage asks how much the supplier matters to the customer.
Filings often discuss concentration without giving both sides of the relationship. Directional metrics make asymmetric dependence visible. The relationship-size versus relative-exposure guide explains why those denominators should remain separate.
A graph can reveal second-order questions the filing never asks
Once the investor knows the named counterparties, new questions become possible. Does another holding depend on the same supplier? Does an upstream supplier also serve a competitor?
Does one customer connect several portfolio holdings? Does a regulatory shock propagate through more than one node? These are network questions.
A company filing is organized around one reporting entity. It is not designed to map the entire economic neighborhood around that entity.
Where filings remain better
Supply-chain data is not a replacement for filings. Filings remain better for audited or reported financial statements, legal commitments, segment disclosures, management risk language, debt, working capital, accounting policy, and contractual terms disclosed by the company. A relationship estimate should not be presented as though it came from the company's audited financial statements. The distinction improves the research rather than weakening it.
Where supply-chain data adds the most
The strongest incremental value tends to appear when the question requires named counterparties, cross-company comparison, relationship direction, relative economic importance, network topology, historical relationship state, private-company connections, and portfolio overlap. Those are precisely the cases where one-company-at-a-time filings become cumbersome.
A practical combined workflow
- Read the filing for the company's own disclosures.
- Identify unresolved supplier, customer, concentration, or network questions.
- Map named relationships.
- Use directional metrics to prioritize the important edges.
- Validate material relationships with public sources where possible.
- Keep anonymous filing disclosures anonymous unless evidence supports an identity.
- Separate reported company facts from relationship estimates.
- Use the network to generate the next research question.
The Altsets methodology explains how relationship evidence and estimates are handled. The Altsets documentation covers the available interfaces for retrieving and exploring relationship data. Browse Supply-Chain Data Use Cases for narrower examples of how filings and network data can be combined.