Kinetic Seas (KSEZ) Operating Expenses (2021 - 2026)
Kinetic Seas (KSEZ) posted Operating Expenses of $242,334 for Q2 2026, down 74.9% from $965,044 a year earlier and down 33.3% from the prior quarter.
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Analysis
Kinetic Seas (KSEZ) Operating Expenses (2021 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Kinetic Seas was $989,864, down 77.2% year-over-year; for FY2025, it came in at $1.55 million, down 59.3% from FY2024.
- Annual Operating Expenses shows a four-year compound annual growth rate of 156.5% (FY2021 to FY2025).
- In prior years, Kinetic Seas' Operating Expenses was $3.82 million in FY2024, $121,538 in FY2023 (+60.7%), $75,653 in FY2022 (+110.7%) and $35,901 in FY2021.
- Quarterly Operating Expenses has run from a low of $1,350 in Q1 2022 to a high of $2.11 million in Q4 2024 over five years.
- On a year-over-year basis, Operating Expenses increased in three of the last six quarters, with an average decline of 8.8%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q3 2022, with growth of 981.1%; the weakest was Q4 2025, with a decline of 93.6%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $363,246 (Q1 2026), $134,453 (Q4 2025) and $249,831 (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 316.55 Bn | 301.63 Bn | 2.30 Bn | 2.13 Bn |
| 2 | CrowdStrike Holdings | 269.03 Bn | 249.47 Bn | 1.10 Bn | 1.13 Bn |
| 3 | Fortinet | 129.08 Bn | 115.01 Bn | 1.64 Bn | 953.90 Mn |
| 4 | Snowflake | 116.42 Bn | 103.73 Bn | 1.04 Bn | 1.30 Bn |
| 5 | Datadog | 96.40 Bn | 78.04 Bn | 881.34 Mn | 875.89 Mn |
| 6 | Okta | 34.24 Bn | 24.34 Bn | 641.00 Mn | 534.00 Mn |
| 7 | Axon Enterprise | 34.08 Bn | 28.61 Bn | 546.45 Mn | 499.67 Mn |
| 8 | Zscaler | 32.34 Bn | 18.46 Bn | - | - |
| 9 | Baidu | 29.50 Bn | -44.13 Bn | 1.47 Mn | 4.17 Bn |
| 10 | Kinetic Seas | 1.82 Mn | 1.82 Mn | 519,750.00 | 242,334.00 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 242,334.00 |
| Mar 31, 2026 | 363,246.00 |
| Dec 31, 2025 | 134,453.00 |
| Sep 30, 2025 | 249,831.00 |
| Jun 30, 2025 | 965,044.00 |
| Mar 31, 2025 | 204,352.00 |
| Dec 31, 2024 | 2.11 Mn |
| Sep 30, 2024 | 1.06 Mn |
| Jun 30, 2024 | 458,213.00 |
| Mar 31, 2024 | 197,501.00 |
| Dec 31, 2023 | 79,261.00 |
| Sep 30, 2023 | 17,345.00 |
| Jun 30, 2023 | 22,205.00 |
| Mar 31, 2023 | 2,726.00 |
| Dec 31, 2022 | 14,588.00 |
| Sep 30, 2022 | 52,790.00 |
| Jun 30, 2022 | 6,925.00 |
| Mar 31, 2022 | 1,350.00 |
| Dec 31, 2021 | 6,333.00 |
| Sep 30, 2021 | 4,883.00 |
API Access
Kinetic Seas 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=operating-expenses&ticker=KSEZ&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "KSEZ", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=KSEZ&period=max&api_key=YOUR_API_KEY");
const data = await res.json();