Datavault AI (DVLT) Non Operating Interest Expenses (2017 - 2026)
Datavault AI (DVLT) posted Non Operating Interest Expenses of $1 million for Q2 2026, down 94.2% from $17.2 million a year earlier and down 10.8% from the prior quarter.
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Analysis
Datavault AI (DVLT) Non Operating Interest Expenses (2017 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Non Operating Interest Expenses at Datavault AI was $4.78 million, down 72.4% year-over-year; for FY2025, it came in at $19.98 million.
- Annual Non Operating Interest Expenses shows a five-year compound annual growth rate of 70.3% (FY2020 to FY2025).
- In prior years, Datavault AI's Non Operating Interest Expenses was $1.27 million in FY2024 (+36.5%), $932,000 in FY2023 (+3.8%), $898,000 in FY2022 and $9,000 in FY2021 (-99.4%).
- Quarterly Non Operating Interest Expenses has run from a low of -$9,000 in Q3 2024 to a high of $17.2 million in Q2 2025 over five years.
- On a year-over-year basis, Non Operating Interest Expenses increased in 1 of the last four quarters, with growth averaging 139.9%.
- The strongest year-over-year quarter for Non Operating Interest Expenses in the past five years was Q1 2026, with growth of 834.2%; the weakest was Q2 2026, with a decline of 94.2%.
- According to Business Quant data, Non Operating Interest Expenses for the three prior quarters was $1.12 million (Q1 2026), $1.8 million (Q4 2025) and $864,000 (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Non Operating Interest Expenses (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 323.81 Bn | 308.88 Bn | 2.30 Bn | - |
| 2 | CrowdStrike Holdings | 271.09 Bn | 251.53 Bn | 1.10 Bn | 6.05 Mn |
| 3 | Fortinet | 131.14 Bn | 117.07 Bn | 1.64 Bn | 3.20 Mn |
| 4 | Snowflake | 119.71 Bn | 107.03 Bn | 1.04 Bn | 2.08 Mn |
| 5 | Datadog | 98.30 Bn | 79.94 Bn | 881.34 Mn | 3.26 Mn |
| 6 | Okta | 34.95 Bn | 25.05 Bn | 641.00 Mn | -19.00 Mn |
| 7 | Axon Enterprise | 34.32 Bn | 28.85 Bn | 546.45 Mn | 28.10 Mn |
| 8 | Zscaler | 32.52 Bn | 18.64 Bn | - | - |
| 9 | Baidu | 29.56 Bn | -44.07 Bn | 1.47 Mn | -90.00 Mn |
| 10 | Datavault AI | 136.71 Mn | 136.71 Mn | 2.88 Mn | 1.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.00 Mn |
| Mar 31, 2026 | 1.12 Mn |
| Dec 31, 2025 | 1.80 Mn |
| Sep 30, 2025 | 864,000.00 |
| Jun 30, 2025 | 17.20 Mn |
| Mar 31, 2025 | 120,000.00 |
| Dec 31, 2024 | 12,000.00 |
| Sep 30, 2024 | -9,000.00 |
| Jun 30, 2024 | 4,000.00 |
| Mar 31, 2024 | 1.27 Mn |
| Dec 31, 2023 | 120,000.00 |
| Sep 30, 2023 | 52,000.00 |
| Jun 30, 2023 | 37,000.00 |
| Mar 31, 2023 | 723,000.00 |
| Dec 31, 2022 | 724,000.00 |
| Sep 30, 2022 | 173,000.00 |
| Mar 31, 2022 | 1,000.00 |
| Sep 30, 2021 | 3,000.00 |
| Jun 30, 2021 | 3,000.00 |
| Mar 31, 2021 | 3,000.00 |
API Access
Datavault AI Non Operating Interest Expenses 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=non-operating-interest-expenses&ticker=DVLT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "non-operating-interest-expenses", "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=non-operating-interest-expenses&ticker=DVLT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();