C3is Inc.: operating income or loss
Operating income or loss for C3is Inc. Inspect selected reporting periods, original units and SEC filing links; download the financial history.
All C3is Inc. financial histories
What this measure means
Operating revenue less operating expenses for the reporting period. It excludes items outside the reported operating result and is not free cash flow.
Exact concept: us-gaap:OperatingIncomeLoss. 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 2023-01-01 to 2025-12-31. The SEC response was captured on 2026-09-21.
Selected filing history
| Period start | Period end | Value | Unit | Filed | Source filing |
|---|---|---|---|---|---|
| 2025-01-01 | 2025-12-31 | 1,364,430 | USD | 2026-04-22 | 20-F · 0001193125-26-170448 |
| 2024-01-01 | 2024-12-31 | 10,061,966 | USD | 2026-04-22 | 20-F · 0001193125-26-170448 |
| 2023-01-01 | 2023-12-31 | 10,427,961 | USD | 2026-04-22 | 20-F · 0001193125-26-170448 |
Related financial histories
- C3is Inc.: total assets
- C3is Inc.: total liabilities
- C3is Inc.: stockholders equity
- C3is Inc.: cash and cash equivalents
- C3is Inc.: net income or loss
- C3is Inc.: operating cash flow
- C3is Inc.: capital expenditure payments
- C3is Inc.: revenue
- C3is Inc.: financing cash flow
- C3is Inc.: investing cash flow
- C3is Inc.: retained earnings or deficit
- C3is Inc.: basic weighted-average shares
- C3is Inc.: diluted weighted-average shares
- C3is Inc.: basic earnings per share
- C3is Inc.: diluted earnings per share
- C3is Inc.: net property, plant and equipment
- C3is Inc.: share-based compensation expense
- C3is Inc.: current assets
- C3is Inc.: current liabilities
- C3is Inc.: operating expenses
- C3is Inc.: net inventory
Inspect the source
- Entity
- C3is Inc. / CIK 0001951067
- Captured
- 2026-09-21T17:36:04.952Z
- SEC response SHA-256
da78fecd21511a9fb874f191811207b146280ddcad5263929138cc60c5fd2ff9
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
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- Inspect the ALPHAC engine on GitHub
- Read the MCP server source and integration examples
Read the published dataset with Python
import json
from urllib.request import urlopen
with urlopen("https://canlicapital.com/company-data/0001951067.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"])))