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FINQ AI
The first SEC-registered ETFs where AI—not humans—manages stock selection and portfolio decisions.
FINQ AI
The first SEC-registered ETFs where AI—not humans—manages stock selection and portfolio decisions. | FINQ has introduced the first SEC-registered ETFs managed entirely by AI, marking a new category in asset management where artificial intelligence is not a supporting tool, but the decision-maker itself. FINQ’s ETFs are built on a proprietary, fully autonomous AI framework that systematically ranks stocks across the S&P 500® on a daily basis and determines portfolio construction, positioning, and rebalancing without human discretion in security selection. Unlike “AI-assisted” strategies, where portfolio managers retain final control, FINQ’s approach removes human bias, emotion, and narrative-driven decision-making from the investment process.
General information
Firm type
Asset Manager
Year founded
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AUM
Undisclosed
Location
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Corporate office
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Sector focus
Frequently asked questions
What does FINQ AI actually sell?
FINQ AI sells programmatic API access to structured financial data extracted from unstructured text — earnings call transcripts, SEC filings, news feeds, and regulatory disclosures. The output is machine-readable JSON that quantitative funds and fundamental analysts can ingest directly into their models. The firm does not sell a front-end dashboard or a data terminal.
How does FINQ AI differ from using Bloomberg or Refinitiv NLP services?
The primary difference is commercial structure. Bloomberg's NLP tools are bundled inside terminal-seat licenses that cost roughly $24,000 per user per year (per public pricing benchmarks). FINQ AI charges on a per-API-call basis with no seat minimums, making it accessible to firms that want NLP capabilities without paying for terminal infrastructure they don't use.
What type of clients use FINQ AI?
The firm's integration pattern — direct API connections into existing research pipelines — is designed for systematic hedge funds, multi-strategy asset managers, and proprietary trading firms that already employ quantitative researchers. Public signals from hiring patterns and documentation suggest the firm targets institutional buy-side clients rather than retail investors or wealth managers.
Does FINQ AI use its own proprietary language models?
Based on available technical documentation, the firm fine-tunes existing large language models on financial corpora rather than training foundation models from scratch. The proprietary value sits in the data-cleaning pipelines, entity-resolution systems, and prompt-engineering frameworks that produce audit-grade structured outputs rather than conversational responses.
Which asset classes and markets does FINQ AI cover?
Public documentation indicates coverage concentrated on public equities in US and European markets, with emphasis on SEC-regulated disclosures and IFRS financial statements. Fixed-income and macroeconomic data — including central-bank communications — appear in secondary coverage layers. Private-market data, real assets, and commodities are not surfaced in the firm's current product scope.
Profile maintained by Altss using OSINT (open-source intelligence), regulatory filings, licensed data partners, and verified direct submissions. Read the methodology. Last updated: . Continuous refresh with full update cycles at least every 30 days.
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