Global AI, Inc.: revenue

What this measure means

Revenue under this specific accounting concept. A missing value is not zero; filers can use other revenue concepts.

Exact concept: us-gaap:Revenues. Each value covers an annual-duration reporting interval, shown with both start and end dates. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2009-10-01 to 2024-12-31. The SEC response was captured on 2026-09-20.

Selected filing history

Related financial histories

• Global AI, Inc.: total assets
• Global AI, Inc.: total liabilities
• Global AI, Inc.: stockholders equity
• Global AI, Inc.: net income or loss
• Global AI, Inc.: operating cash flow
• Global AI, Inc.: contract revenue excluding tax
• Global AI, Inc.: financing cash flow
• Global AI, Inc.: investing cash flow
• Global AI, Inc.: retained earnings or deficit
• Global AI, Inc.: basic weighted-average shares
• Global AI, Inc.: diluted weighted-average shares
• Global AI, Inc.: basic earnings per share
• Global AI, Inc.: diluted earnings per share
• Global AI, Inc.: operating income or loss
• Global AI, Inc.: current assets
• Global AI, Inc.: interest expense
• Global AI, Inc.: current liabilities
• Global AI, Inc.: current accounts payable
• Global AI, Inc.: net current accounts receivable
• Global AI, Inc.: operating expenses
• Global AI, Inc.: gross profit
• Global AI, Inc.: research and development expense

Inspect the source

Entity

Global AI, Inc. / CIK 0001473490

Captured

2026-09-20T09:07:52.351Z

SEC response SHA-256

b3c8233dbad8337f1890ab8018c7722ce5fea933dbc84059d62162eb896c7fe5

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.

Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.

Use this in research

A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.

These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.

Research methodology · Execution and cost assumptions · Check backtest overfitting

Build with the open-source tools

Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.

• Get an API key and run your first validation
• Connect the MCP server to your coding assistant
• Inspect the ALPHAC engine on GitHub
• Read the MCP server source and integration examples

import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0001473490.json") as response:
    record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
    print(concept["tag"], next(iter(concept["observations"])))