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Air Industries Group: total liabilities

Air Industries Group total liabilities: $39.1 million at 2025-12-31, up 8.5% on the year. 15 values since 2011 from SEC filings, each linked to its filing.

All Air Industries Group financial histories

At a glance

Air Industries Group reported total liabilities of $39.1 million at 2025-12-31, up 8.5% from $36.1 million a year earlier. From 2011 to 2025 it grew at a compound 1.4% a year, from $32.3 million to $39.1 million. Across the last five reported years it ranged from $35.5 million (2023-12-31) to $39.1 million (2025-12-31). That was 67.1% of total assets ($58.3 million) at the same date.

Computed from the values in the table below, in USD; each links to the filing it came from.

What this measure means

Recognized obligations at the reporting date. The definition and scope differ from interest-bearing debt.

Exact concept: us-gaap:Liabilities. 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 2011-12-31 to 2025-12-31. The SEC response was captured on 2026-09-20.

Selected filing history

Total liabilities in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
-2025-12-3139,128,000USD2026-03-2710-K · 0001213900-26-035731 SEC
-2024-12-3136,063,000USD2026-03-2710-K · 0001213900-26-035731 SEC
-2023-12-3135,525,000USD2025-04-1510-K · 0001213900-25-031944 SEC
-2022-12-3136,975,000USD2024-04-1510-K · 0001213900-24-033018 SEC
-2021-12-3136,036,000USD2023-05-1610-K · 0001213900-23-040540 SEC
-2020-12-3142,668,000USD2022-03-2510-K · 0001213900-22-015031 SEC
-2019-12-3140,884,000USD2021-03-2910-K · 0001213900-21-018136 SEC
-2018-12-3136,150,000USD2020-03-2710-K · 0001213900-20-007657 SEC
-2017-12-3142,989,000USD2019-06-0410-K/A · 0001213900-19-010014 SEC
-2016-12-3157,910,000USD2018-04-1910-K/A · 0001193805-18-000558 SEC
-2015-12-3159,445,000USD2017-04-2110-K · 0001193805-17-000671 SEC
-2014-12-3137,908,000USD2016-04-0410-K · 0001193805-16-003011 SEC
-2013-12-3128,559,000USD2015-03-3110-K · 0001193805-15-000450 SEC
-2012-12-3134,168,000USD2014-03-2510-K · 0001193805-14-000587 SEC
-2011-12-3132,315,000USD2013-03-2910-K · 0001193805-13-000723 SEC

Related AIR INDUSTRIES GROUP histories

All 57 Air Industries Group histories

Inspect the source

Entity
AIR INDUSTRIES GROUP / CIK 0001009891
Captured
SEC response SHA-256
59d060c3e3a47187bffcc59b02c15fa4e6befed41accdf89fac001b3e7f2a1b9

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.

The MCP server is free and MIT-licensed: npx -y canli-mcp. If these records help your research, a star on GitHub helps other researchers find them.

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

with urlopen("https://canlicapital.com/company-data/0001009891.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"])))