Kinetic Seas (KSEZ) Total Liabilities (2021 - 2026)
Kinetic Seas (KSEZ) posted Total Liabilities of $9.84 million for Q2 2026, up 406.3% from $1.94 million a year earlier but down 5.0% from the prior quarter.
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Analysis
Kinetic Seas (KSEZ) Total Liabilities (2021 - 2026) Analysis & Trends
At the end of FY2025, Kinetic Seas' Total Liabilities came in at $10.96 million, up 395.3% from FY2024.
- Annual Total Liabilities has increased for four consecutive years, with a four-year compound annual growth rate of 258.1% (FY2021 to FY2025).
- In prior years, Kinetic Seas' Total Liabilities was $2.21 million in FY2024 (+876.5%), $226,584 in FY2023 (+43.8%), $157,525 in FY2022 (+136.2%) and $66,681 in FY2021.
- Quarterly Total Liabilities has run from a low of $66,681 in Q4 2021 to a high of $10.96 million in Q4 2025 over five years.
- On a year-over-year basis, Total Liabilities has increased in each of the last 12 quarters, with growth averaging 405.2% over the last eight quarters.
- Over the past five years, the year-over-year growth in Total Liabilities ranged from 41.4% (Q1 2024) to 876.5% (Q4 2024).
- According to Business Quant data, Total Liabilities for the three prior quarters was $10.35 million (Q1 2026), $10.96 million (Q4 2025) and $1 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 316.55 Bn | 301.63 Bn | 2.30 Bn | 20.97 Bn |
| 2 | CrowdStrike Holdings | 269.03 Bn | 249.47 Bn | 1.10 Bn | 6.89 Bn |
| 3 | Fortinet | 129.08 Bn | 115.01 Bn | 1.64 Bn | 9.31 Bn |
| 4 | Snowflake | 116.42 Bn | 103.73 Bn | 1.04 Bn | 6.54 Bn |
| 5 | Datadog | 96.40 Bn | 78.04 Bn | 881.34 Mn | 3.18 Bn |
| 6 | Okta | 34.24 Bn | 24.34 Bn | 641.00 Mn | 2.17 Bn |
| 7 | Axon Enterprise | 34.08 Bn | 28.61 Bn | 546.45 Mn | 3.81 Bn |
| 8 | Zscaler | 32.34 Bn | 18.46 Bn | - | 5.27 Bn |
| 9 | Baidu | 29.50 Bn | -44.13 Bn | 1.47 Mn | 27.69 Bn |
| 10 | Kinetic Seas | 1.82 Mn | 1.82 Mn | 519,750.00 | 9.84 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 9.84 Mn |
| Mar 31, 2026 | 10.35 Mn |
| Dec 31, 2025 | 10.96 Mn |
| Sep 30, 2025 | 1.00 Mn |
| Jun 30, 2025 | 1.94 Mn |
| Mar 31, 2025 | 1.35 Mn |
| Dec 31, 2024 | 2.21 Mn |
| Sep 30, 2024 | 487,207.00 |
| Jun 30, 2024 | 578,502.00 |
| Mar 31, 2024 | 250,034.00 |
| Dec 31, 2023 | 226,584.00 |
| Sep 30, 2023 | 226,127.00 |
| Jun 30, 2023 | 199,278.00 |
| Mar 31, 2023 | 176,826.00 |
| Dec 31, 2022 | 157,525.00 |
| Sep 30, 2022 | 136,330.00 |
| Dec 31, 2021 | 66,681.00 |
API Access
Kinetic Seas Total 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-liabilities&ticker=KSEZ&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "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=total-liabilities&ticker=KSEZ&period=max&api_key=YOUR_API_KEY");
const data = await res.json();