NetClass Technology (NTCL) Cash & Equivalents (2023 - 2026)
NetClass Technology's Cash & Equivalents was $1.7 million in the quarter ended Mar 31, 2026, down 26.3% from $2.31 million a year earlier.
NetClass Technology (NTCL) Cash & Equivalents (2023 - 2026) Analysis & Trends
As of Sep 30, 2025, Cash & Equivalents at NetClass Technology came in at $1.76 million, up 329.5% from the prior year.
- Cash & Equivalents shows a three-year compound annual growth rate of 103.9% (years ended Sep 2022 to Sep 2025).
- In earlier years, Cash & Equivalents was $410,716 in the year ended Sep 30, 2024 (-21.7%), $524,601 in the year ended Sep 30, 2023 (+152.0%) and $208,206 in the year ended Sep 30, 2022.
- The figure for the quarter ended Mar 31, 2026 marks the lowest quarterly Cash & Equivalents since the quarter ended Sep 30, 2024.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cash & Equiv. (Qtr) |
|---|---|---|---|---|---|
| 1 | Bryn | 945.00 Bn | 945.00 Bn | - | - |
| 2 | Veeva Systems | 45.65 Bn | 17.89 Bn | 695.95 Mn | 1.81 Bn |
| 3 | Samsara | 23.42 Bn | 20.19 Bn | 392.58 Mn | 291.39 Mn |
| 4 | Toast | 16.88 Bn | 9.55 Bn | 516.00 Mn | 1.02 Bn |
| 5 | Ptc | 16.22 Bn | 15.03 Bn | 490.47 Mn | 351.45 Mn |
| 6 | Duolingo | 13.71 Bn | 8.88 Bn | 216.74 Mn | 1.18 Bn |
| 7 | Trimble | 13.42 Bn | 12.48 Bn | 674.90 Mn | 214.40 Mn |
| 8 | Manhattan Associates | 11.90 Bn | 10.90 Bn | 168.33 Mn | 186.11 Mn |
| 9 | Costar | 11.23 Bn | 5.20 Bn | 728.00 Mn | 1.27 Bn |
| 10 | NetClass Technology | 712,489.15 | -5.35 Mn | - | 1.70 Mn |
Historic Data
| Date | Value |
|---|---|
| Mar 31, 2026 | 1.70 Mn |
| Sep 30, 2025 | 1.76 Mn |
| Mar 31, 2025 | 2.31 Mn |
| Sep 30, 2024 | 410,716.00 |
| Sep 30, 2023 | 524,601.00 |
NetClass Technology Cash & Equivalents 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=cash-and-equivalents&ticker=NTCL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cash-and-equivalents", "ticker": "NTCL", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=cash-and-equivalents&ticker=NTCL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();