Soundthinking (SSTI) Total Current Liabilities (2016 - 2026)
Soundthinking (SSTI) posted Total Current Liabilities of $47.61 million for Q2 2026, down 10.1% from $52.98 million a year earlier and down 9.4% from the prior quarter.
Soundthinking (SSTI) Total Current Liabilities (2016 - 2026) Analysis & Trends
At the end of FY2025, Soundthinking's Total Current Liabilities came in at $57.4 million, up 2.4% from FY2024.
- Annual Total Current Liabilities shows a five-year compound annual growth rate of 13.1% (FY2020 to FY2025).
- In prior years, Soundthinking's Total Current Liabilities was $56.06 million in FY2024 (-6.3%), $59.82 million in FY2023 (+11.8%), $53.51 million in FY2022 (+55.1%) and $34.5 million in FY2021 (+11.4%).
- The Q2 2026 figure stands as the lowest quarterly Total Current Liabilities since Q1 2023.
- On a year-over-year basis, Total Current Liabilities increased in two of the last eight quarters, with an average decline of 6.0%.
- The strongest year-over-year quarter for Total Current Liabilities in the past five years was Q2 2022, with growth of 82.4%; the weakest was Q2 2025, with a decline of 13.0%.
- According to Business Quant data, Total Current Liabilities for the three prior quarters was $52.57 million (Q1 2026), $57.4 million (Q4 2025) and $54.01 million (Q3 2025).
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 | Soundthinking | 72.01 Mn | 23.72 Mn | 11.54 Mn | 47.61 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 47.61 Mn |
| Mar 31, 2026 | 52.57 Mn |
| Dec 31, 2025 | 57.40 Mn |
| Sep 30, 2025 | 54.01 Mn |
| Jun 30, 2025 | 52.98 Mn |
| Mar 31, 2025 | 54.66 Mn |
| Dec 31, 2024 | 56.06 Mn |
| Sep 30, 2024 | 59.60 Mn |
| Jun 30, 2024 | 60.87 Mn |
| Mar 31, 2024 | 61.18 Mn |
| Dec 31, 2023 | 59.82 Mn |
| Sep 30, 2023 | 57.99 Mn |
| Jun 30, 2023 | 47.81 Mn |
| Mar 31, 2023 | 44.79 Mn |
| Dec 31, 2022 | 53.51 Mn |
| Sep 30, 2022 | 45.12 Mn |
| Jun 30, 2022 | 45.56 Mn |
| Mar 31, 2022 | 49.29 Mn |
| Dec 31, 2021 | 34.50 Mn |
| Sep 30, 2021 | 28.53 Mn |
Soundthinking 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=SSTI&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-current-liabilities", "ticker": "SSTI", "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=SSTI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();