Soundthinking (SSTI) Operating Expenses (2016 - 2026)
Soundthinking (SSTI) recorded Operating Expenses of $16.19 million in Q2 2026, down 3.3% from $16.74 million a year earlier and down 10.6% from the prior quarter.
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Analysis
Soundthinking (SSTI) Operating Expenses (2016 - 2026) Analysis & Trends
On a TTM basis, Soundthinking's Operating Expenses came in at $65.14 million as of Jun 30, 2026, down 1.8% year-over-year; for FY2025, it came in at $65.37 million, down 0.6% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 20.5% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $65.74 million in FY2024 (+21.8%), $53.97 million in FY2023 (+38.2%), $39.04 million in FY2022 (+6.7%) and $36.59 million in FY2021 (+42.5%).
- Quarterly Operating Expenses has ranged from $6.23 million in Q3 2022 to $18.12 million in Q1 2026 over the past five years.
- On a year-over-year basis, Operating Expenses rose in five of the last eight quarters, with growth averaging 6.4%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 144.6% in Q3 2023, against a decline of 30.3% in Q3 2022 at the low end.
- Per Business Quant, the preceding three quarters came in at $18.12 million (Q1 2026), $15.14 million (Q4 2025) and $15.69 million (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 | Soundthinking | 108.07 Mn | 59.79 Mn | 11.54 Mn | 16.19 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 16.19 Mn |
| Mar 31, 2026 | 18.12 Mn |
| Dec 31, 2025 | 15.14 Mn |
| Sep 30, 2025 | 15.69 Mn |
| Jun 30, 2025 | 16.74 Mn |
| Mar 31, 2025 | 17.80 Mn |
| Dec 31, 2024 | 15.51 Mn |
| Sep 30, 2024 | 16.26 Mn |
| Jun 30, 2024 | 16.12 Mn |
| Mar 31, 2024 | 17.50 Mn |
| Dec 31, 2023 | 10.61 Mn |
| Sep 30, 2023 | 15.23 Mn |
| Jun 30, 2023 | 15.01 Mn |
| Mar 31, 2023 | 13.11 Mn |
| Dec 31, 2022 | 11.87 Mn |
| Sep 30, 2022 | 6.23 Mn |
| Jun 30, 2022 | 8.45 Mn |
| Mar 31, 2022 | 12.49 Mn |
| Dec 31, 2021 | 10.65 Mn |
| Sep 30, 2021 | 8.94 Mn |
API Access
Soundthinking 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=SSTI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "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=operating-expenses&ticker=SSTI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();