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VisionSys AI Inc: financial reference

Explore VisionSys AI Inc financial histories from SEC filings, with original units, reporting periods, filing dates and downloadable source data.

Reported financial histories

Choose a measure to inspect its definition, complete selected history and filing provenance. Each row shows the latest period available for that selected concept and original unit. Separate currencies and reporting intervals remain separate rows. Coverage dates can differ between concepts. A recent capture does not imply recent accounting coverage; these amounts are not prices.

Latest periods by selected concept and original unit
MeasurePeriod startPeriod endValueUnitFiled
Total assetsAt date2025-12-31106,562,000CNY2026-05-11
Total assetsAt date2025-12-3115,238,000USD2026-05-11
Total liabilitiesAt date2025-12-313,820,000CNY2026-05-11
Total liabilitiesAt date2025-12-31546,000USD2026-05-11
Stockholders equityAt date2025-12-31102,742,000CNY2026-05-11
Stockholders equityAt date2025-12-3114,692,000USD2026-05-11
Cash and cash equivalentsAt date2025-12-3154,986,000CNY2026-05-11
Cash and cash equivalentsAt date2025-12-317,863,000USD2026-05-11
Net income or loss2025-01-012025-12-311,718,870,000CNY2026-05-11
Net income or loss2025-01-012025-12-31245,796,000USD2026-05-11
Operating cash flow2025-01-012025-12-31-188,104,000CNY2026-05-11
Operating cash flow2025-01-012025-12-31-26,898,000USD2026-05-11
Capital expenditure payments2017-01-012017-12-31177,251,000CNY2018-04-30
Capital expenditure payments2015-01-012015-12-3116,053,871USD2016-04-20
Contract revenue excluding tax2024-01-012024-12-311,170,858,000CNY2025-05-15
Contract revenue excluding tax2024-01-012024-12-31160,407,000USD2025-05-15
Financing cash flow2025-01-012025-12-31139,529,000CNY2026-05-11
Financing cash flow2025-01-012025-12-3119,952,000USD2026-05-11
Investing cash flow2025-01-012025-12-31-76,452,000CNY2026-05-11
Investing cash flow2025-01-012025-12-31-10,932,000USD2026-05-11
Retained earnings or deficitAt date2025-12-31-1,295,645,000CNY2026-05-11
Retained earnings or deficitAt date2025-12-31-185,275,000USD2026-05-11
Basic weighted-average shares2025-01-012025-12-31193,836,988shares2026-05-11
Diluted weighted-average shares2025-01-012025-12-31193,836,988shares2026-05-11
Basic earnings per share2022-01-012022-12-317.64CNY/shares2023-04-28
Basic earnings per share2022-01-012022-12-311.11USD/shares2023-04-28
Diluted earnings per share2022-01-012022-12-317.23CNY/shares2023-04-28
Diluted earnings per share2022-01-012022-12-311.05USD/shares2023-04-28
Income tax expense or benefit2024-01-012024-12-3131,492,000CNY2025-05-15
Income tax expense or benefit2024-01-012024-12-314,314,000USD2025-05-15
Net property, plant and equipmentAt date2024-12-3121,591,000CNY2025-05-15
Net property, plant and equipmentAt date2024-12-312,958,000USD2025-05-15
Share-based compensation expense2024-01-012024-12-311,341,000CNY2025-05-15
Share-based compensation expense2024-01-012024-12-31183,000USD2025-05-15
Operating income or loss2025-01-012025-12-31-39,981,000CNY2026-05-11
Operating income or loss2025-01-012025-12-31-5,717,000USD2026-05-11
Current assetsAt date2025-12-3155,132,000CNY2026-05-11
Current assetsAt date2025-12-317,884,000USD2026-05-11
Current liabilitiesAt date2025-12-313,820,000CNY2026-05-11
Current liabilitiesAt date2025-12-31546,000USD2026-05-11
Current accounts payableAt date2024-12-315,971,000CNY2025-05-15
Current accounts payableAt date2024-12-31818,000USD2025-05-15
Goodwill carrying amountAt date2023-12-3149,416,000CNY2025-05-15
Goodwill carrying amountAt date2023-12-316,960,000USD2024-04-19
Net current accounts receivableAt date2022-12-3168,733,000CNY2023-04-28
Net current accounts receivableAt date2022-12-319,965,000USD2023-04-28
Common-stock repurchase payments2024-01-012024-12-317,360,000CNY2026-05-11
Common-stock repurchase payments2024-01-012024-12-311,008,000USD2025-05-15
Net inventoryAt date2024-12-3110,475,000CNY2025-05-15
Gross profit2025-01-012025-12-31229,000CNY2026-05-11
Gross profit2025-01-012025-12-3133,000USD2026-05-11
Cost of revenue2025-01-012025-12-31810,000CNY2026-05-11
Cost of revenue2025-01-012025-12-31116,000USD2026-05-11
Research and development expense2024-01-012024-12-3119,101,000CNY2025-05-15
Research and development expense2024-01-012024-12-312,617,000USD2025-05-15

Inspect the source

Entity
VisionSys AI Inc / CIK 0001592560
Captured
2026-09-20T09:24:19.062Z
SEC response SHA-256
5919c855b0988061fb2346196c3c9680aae00f1513514d6cc0ac4fe74232a035

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.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0001592560.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"])))