Everything we build stands on this.

The Ontology engine classifies markets across asset classes, by drivers such as revenue, supply chains, customers and regulators. Experts in each industry define the categories.

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Exposure, classified and in plain sight.

Reclassifies

7

identity layers

Every holding, across five asset classes, by what actually drives its business.

Connects

40+

datasets

Each holding to the macro, policy, and fundamental data behind it.

Refreshes

10,000+

dynamic exposures

Exposures are re-derived quarterly, based on earnings calls and market changes.

The economy moved. The boxes didn’t.

Industry classifications were designed last century. Those labels flow into the ETFs and models your clients own, so portfolios that look diversified often aren’t.

What legacy labels show

One label per company.
  • AmazonConsumer Discretionary
  • NetflixCommunication Services
  • Eli LillyHealth Care
  • JPMorgan ChaseFinancials

Amazon shares exposures with 10 companies in the network

Amazon · Legacy label: Consumer Discretionary

What LAN.Q sees

What Amazon actually depends on.

AI Compute & Data Center Infrastructure Buildout

Revenue rides on how much the largest cloud companies spend on AI chips, servers and data centers.

US China Trade Policy & Tariff Risk

Tariffs on goods and parts moving between the US and China change costs and supply routes.

For illustrative and educational purposes only.

Same input, same answer. Every time.

Defined by experts

Categories set by people who know each industry.

Every category was defined by subject-matter experts across each industry, then applied to every holding.

Deterministic engine

Every exposure can be traced.

The same input always gives the same answer, so any result can be traced, repeated and defended. Ask how we reached 60% AI exposure, and we show you each step.

IRC Section 351 and prospectus

One language from analysis to prospectus.

The categories that analyze an IRC Section 351 exchange also write the fund prospectus, so the thesis matches the holdings. Standardized language cuts drafting and review time.

One classification layer, three ways in.

For funds

Describe, compare, and position your strategy.

Standard language means standard risk disclosures, and faster prospectus review. The Ontology powers our fund benchmarking and prospectus drafting.

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For advisors

See what client portfolios really hold.

The Ontology is the engine under LAN.Q. It brings concentration, hidden risk and gaps across client portfolios into your workflow in minutes.

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For builders · Partnerships

Customized software, built on LAN.Q.

License the Ontology for your own research, indexes or products, or have us build custom software on top of it, as a partnership.

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Questions about the Ontology.

What is the Ontology?

The Ontology engine classifies markets across asset classes, by drivers such as revenue, supply chains, customers and regulators. Experts in each industry define the categories.

How is it different from legacy industry labels?

Legacy industry classifications were designed last century and put each company in one fixed box. The Ontology classifies holdings by what actually drives revenue, supply chains, customers and regulation, and re-derives exposures every quarter.

Who defines the categories?

Subject-matter experts in each industry, across every asset class. Each category is then applied to every holding.

Will I get the same answer twice?

Yes. The engine is deterministic: the same input always gives the same answer, so any result can be traced, repeated and defended.

What does the Ontology cover?

Global asset classes: equities, fixed income, commodities, FX and REITs, connected to 40+ datasets and refreshed quarterly.

Can I license the Ontology?

Yes. You can license the classification data for your own research, indexes or products, or have Langar build custom software on top of it as a partnership.

Talk to us about licensing.

Use the classification data in your own research, indexes, or products. Tell us what you’re building.

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