Datavault AI Inc.: retained earnings or deficit
Retained earnings or deficit for Datavault AI Inc. Inspect selected reporting periods, original units and SEC filing links; download the financial history.
All Datavault AI Inc. financial histories
What this measure means
Accumulated undistributed earnings or deficit at the reporting date. This balance is not cash available for distribution.
Exact concept: us-gaap:RetainedEarningsAccumulatedDeficit. Each value is a balance at the reporting date, not a flow earned over a year. Different units remain separate; no currency conversion or interpolation is applied.
Coverage of this history
Selected reporting periods run from 2017-12-31 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 |
|---|---|---|---|---|---|
| At date | 2025-12-31 | -377,445,000 | USD | 2026-03-18 | 10-K · 0001104659-26-031280 |
| At date | 2024-12-31 | -298,451,000 | USD | 2026-03-18 | 10-K · 0001104659-26-031280 |
| At date | 2023-12-31 | -247,042,000 | USD | 2025-03-31 | 10-K · 0001410578-25-000600 |
| At date | 2022-12-31 | -228,321,000 | USD | 2024-04-01 | 10-K · 0001410578-24-000412 |
| At date | 2021-12-31 | -212,203,000 | USD | 2023-03-17 | 10-K · 0001410578-23-000276 |
| At date | 2020-12-31 | -200,383,000 | USD | 2022-03-11 | 10-K · 0001410578-22-000337 |
| At date | 2019-12-31 | -187,678,000 | USD | 2021-03-16 | 10-K · 0001104659-21-036564 |
| At date | 2018-12-31 | -175,640,000 | USD | 2020-03-25 | 10-K · 0001104659-20-037958 |
| At date | 2017-12-31 | -108,283,423 | USD | 2019-03-29 | 10-K · 0001144204-19-016754 |
Related financial histories
- Datavault AI Inc.: total assets
- Datavault AI Inc.: total liabilities
- Datavault AI Inc.: stockholders equity
- Datavault AI Inc.: cash and cash equivalents
- Datavault AI Inc.: net income or loss
- Datavault AI Inc.: operating cash flow
- Datavault AI Inc.: capital expenditure payments
- Datavault AI Inc.: revenue
- Datavault AI Inc.: financing cash flow
- Datavault AI Inc.: investing cash flow
- Datavault AI Inc.: basic weighted-average shares
- Datavault AI Inc.: diluted weighted-average shares
- Datavault AI Inc.: basic earnings per share
- Datavault AI Inc.: diluted earnings per share
- Datavault AI Inc.: income tax expense or benefit
- Datavault AI Inc.: net property, plant and equipment
- Datavault AI Inc.: share-based compensation expense
- Datavault AI Inc.: operating income or loss
- Datavault AI Inc.: current assets
- Datavault AI Inc.: interest expense
- Datavault AI Inc.: current liabilities
- Datavault AI Inc.: current accounts payable
- Datavault AI Inc.: net finite-lived intangible assets
- Datavault AI Inc.: net current accounts receivable
- Datavault AI Inc.: operating expenses
- Datavault AI Inc.: net inventory
- Datavault AI Inc.: gross profit
- Datavault AI Inc.: cost of revenue
- Datavault AI Inc.: research and development expense
Inspect the source
- Entity
- Datavault AI Inc. / CIK 0001682149
- Captured
- 2026-09-21T17:25:02.265Z
- SEC response SHA-256
327fd05cedf221f88a1af50c26c7004414f2b5261aff4be74209a427d1e2c531
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
Read the published dataset with Python
import json
from urllib.request import urlopen
with urlopen("https://canlicapital.com/company-data/0001682149.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"])))