Datavault AI (DVLT) Other Operating Expenses (2017 - 2026)
Datavault AI (DVLT) recorded Other Operating Expenses of $7.18 million in Q2 2026, up 312.4% from $1.74 million a year earlier and up 8.3% from the prior quarter.
Datavault AI (DVLT) Other Operating Expenses (2017 - 2026) Analysis & Trends
On a TTM basis, Datavault AI's Other Operating Expenses came in at $21.86 million as of Jun 30, 2026, up 303.6% year-over-year; for FY2025, it was $11.28 million, up 183.8% from FY2024.
- Annual Other Operating Expenses has a five-year compound annual growth rate of 30.6% (FY2020 to FY2025).
- Across earlier years, Other Operating Expenses came in at $3.97 million in FY2024 (-23.2%), $5.18 million in FY2023 (-15.7%), $6.14 million in FY2022 (+48.9%) and $4.12 million in FY2021 (+38.6%).
- The Q2 2026 figure is the highest quarterly Other Operating Expenses in data going back to Q2 2017.
- On a year-over-year basis, Other Operating Expenses has increased for six consecutive quarters, with growth averaging 160.8% over the last eight quarters.
- Peak year-over-year performance for Other Operating Expenses in the last five years was growth of 387.3% in Q4 2025, against a decline of 30.0% in Q3 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at $6.64 million (Q1 2026), $5.83 million (Q4 2025) and $2.21 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (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 |
| 3 | Fortinet | 131.14 Bn | 117.07 Bn | 1.64 Bn |
| 4 | Snowflake | 119.71 Bn | 107.03 Bn | 1.04 Bn |
| 5 | Datadog | 98.30 Bn | 79.94 Bn | 881.34 Mn |
| 6 | Okta | 34.95 Bn | 25.05 Bn | 641.00 Mn |
| 7 | Axon Enterprise | 34.32 Bn | 28.85 Bn | 546.45 Mn |
| 8 | Zscaler | 32.52 Bn | 18.64 Bn | - |
| 9 | Baidu | 29.56 Bn | -44.07 Bn | 1.47 Mn |
| 10 | Datavault AI | 136.71 Mn | 136.71 Mn | 2.88 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 7.18 Mn |
| Mar 31, 2026 | 6.64 Mn |
| Dec 31, 2025 | 5.83 Mn |
| Sep 30, 2025 | 2.21 Mn |
| Jun 30, 2025 | 1.74 Mn |
| Mar 31, 2025 | 1.50 Mn |
| Dec 31, 2024 | 1.20 Mn |
| Sep 30, 2024 | 983,000.00 |
| Jun 30, 2024 | 865,000.00 |
| Mar 31, 2024 | 929,000.00 |
| Dec 31, 2023 | 1.39 Mn |
| Sep 30, 2023 | 1.40 Mn |
| Jun 30, 2023 | 1.09 Mn |
| Mar 31, 2023 | 1.29 Mn |
| Dec 31, 2022 | 1.98 Mn |
| Sep 30, 2022 | 1.54 Mn |
| Jun 30, 2022 | 1.33 Mn |
| Mar 31, 2022 | 1.30 Mn |
| Dec 31, 2021 | 1.25 Mn |
| Sep 30, 2021 | 1.02 Mn |
Datavault AI Other Operating 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=other-operating-expenses&ticker=DVLT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-operating-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=other-operating-expenses&ticker=DVLT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();