Datavault AI (DVLT) Total Current Liabilities (2017 - 2026)
Datavault AI (DVLT) posted Total Current Liabilities of $27.27 million for Q2 2026, up 235.9% from $8.12 million a year earlier and up 18.4% from the prior quarter.
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Analysis
Datavault AI (DVLT) Total Current Liabilities (2017 - 2026) Analysis & Trends
At the end of FY2025, Datavault AI's Total Current Liabilities came in at $26.88 million, up 553.6% from FY2024.
- Annual Total Current Liabilities shows a five-year compound annual growth rate of 63.7% (FY2020 to FY2025).
- In prior years, Datavault AI's Total Current Liabilities was $4.11 million in FY2024 (+13.1%), $3.64 million in FY2023 (-1.0%), $3.67 million in FY2022 (+23.9%) and $2.97 million in FY2021 (+29.8%).
- The Q2 2026 figure stands as the highest quarterly Total Current Liabilities since Q2 2018.
- On a year-over-year basis, Total Current Liabilities has increased in each of the last five quarters, with growth averaging 254.2% over the last eight quarters.
- The strongest year-over-year quarter for Total Current Liabilities in the past five years was Q3 2025, with growth of 673.6%; the weakest was Q2 2022, with a decline of 35.3%.
- According to Business Quant data, Total Current Liabilities for the three prior quarters was $23.02 million (Q1 2026), $26.88 million (Q4 2025) and $24.16 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 319.55 Bn | 304.63 Bn | 2.30 Bn | 9.92 Bn |
| 2 | CrowdStrike Holdings | 265.46 Bn | 245.90 Bn | 1.10 Bn | 4.43 Bn |
| 3 | Fortinet | 129.36 Bn | 115.29 Bn | 1.64 Bn | 4.84 Bn |
| 4 | Snowflake | 115.65 Bn | 102.97 Bn | 1.04 Bn | 3.72 Bn |
| 5 | Datadog | 96.45 Bn | 78.09 Bn | 881.34 Mn | 1.87 Bn |
| 6 | Axon Enterprise | 34.50 Bn | 29.03 Bn | 546.45 Mn | 1.40 Bn |
| 7 | Okta | 33.79 Bn | 23.89 Bn | 641.00 Mn | 2.03 Bn |
| 8 | Zscaler | 32.51 Bn | 18.63 Bn | - | 2.96 Bn |
| 9 | Baidu | 29.59 Bn | -44.04 Bn | 1.47 Mn | 13.13 Bn |
| 10 | Datavault AI | 136.71 Mn | 136.71 Mn | 2.88 Mn | 27.27 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 27.27 Mn |
| Mar 31, 2026 | 23.02 Mn |
| Dec 31, 2025 | 26.88 Mn |
| Sep 30, 2025 | 24.16 Mn |
| Jun 30, 2025 | 8.12 Mn |
| Mar 31, 2025 | 4.17 Mn |
| Dec 31, 2024 | 4.11 Mn |
| Sep 30, 2024 | 3.12 Mn |
| Jun 30, 2024 | 3.57 Mn |
| Mar 31, 2024 | 4.35 Mn |
| Dec 31, 2023 | 3.64 Mn |
| Sep 30, 2023 | 3.79 Mn |
| Jun 30, 2023 | 1.91 Mn |
| Mar 31, 2023 | 3.24 Mn |
| Dec 31, 2022 | 3.67 Mn |
| Sep 30, 2022 | 3.86 Mn |
| Jun 30, 2022 | 2.70 Mn |
| Mar 31, 2022 | 3.83 Mn |
| Dec 31, 2021 | 2.97 Mn |
| Sep 30, 2021 | 2.87 Mn |
API Access
Datavault AI Total Current Liabilities API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=total-current-liabilities&ticker=DVLT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-current-liabilities", "ticker": "DVLT", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=total-current-liabilities&ticker=DVLT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();