Zeo ScientifiX (ZEOX) Operating Expenses (2012 - 2026)
Zeo ScientifiX's Operating Expenses came in at $2.6 million for fiscal Q2 2026 (quarter ended Apr 30, 2026), up 11.6% from $2.33 million a year earlier and up 26.0% from the prior quarter.
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Analysis
Zeo ScientifiX (ZEOX) Operating Expenses (2012 - 2026) Analysis & Trends
Over the trailing twelve months to Apr 30, 2026, Zeo ScientifiX reported Operating Expenses of $9.88 million, up 9.6% year-over-year; for FY2025 (ended Oct 31, 2025), it was $9.75 million, up 5.3% from FY2024.
- Operating Expenses carries a five-year compound annual growth rate of -8.4% (FY2020 to FY2025).
- Going back by fiscal year, Operating Expenses was $9.26 million in FY2024 (-14.4%), $10.82 million in FY2023 (-25.8%), $14.58 million in FY2022 (-18.1%) and $17.79 million in FY2021 (+17.9%).
- The five-year range for quarterly Operating Expenses is $2.06 million (fiscal Q1 2026) to $4.36 million (fiscal Q4 2022).
- Year-over-year, Operating Expenses increased in two of the last eight quarters, with growth averaging 2.4%.
- The fastest year-over-year change in Operating Expenses over five years came in fiscal Q4 2022 (growth of 73.4%), and the weakest in fiscal Q1 2022 (a decline of 67.0%).
- Business Quant data shows ZEOX's Operating Expenses at $2.06 million (Q1 2026), $2.07 million (Q4 2025) and $3.15 million (Q3 2025) in the three fiscal quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,230.11 Bn | 1,198.70 Bn | 19.71 Bn | 7.95 Bn |
| 2 | Johnson & Johnson | 644.39 Bn | 564.25 Bn | 17.30 Bn | 11.12 Bn |
| 3 | AbbVie | 503.52 Bn | 476.68 Bn | 12.70 Bn | 10.56 Bn |
| 4 | Merck | 363.29 Bn | 317.72 Bn | 12.21 Bn | 12.80 Bn |
| 5 | Novartis Ag | 298.23 Bn | 262.62 Bn | 11.24 Bn | 6.09 Bn |
| 6 | Astrazeneca | 267.53 Bn | 241.29 Bn | 12.86 Bn | 9.70 Bn |
| 7 | Amgen | 241.80 Bn | 197.20 Bn | 7.24 Bn | 6.54 Bn |
| 8 | Gilead Sciences | 195.07 Bn | 169.19 Bn | 6.22 Bn | 18.20 Bn |
| 9 | Pfizer | 173.33 Bn | 120.28 Bn | 10.94 Bn | 6.68 Bn |
| 10 | Zeo ScientifiX | 7.01 Mn | 3.60 Mn | 2.06 Mn | 2.60 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Apr 30, 2026 | 2.60 Mn |
| Jan 31, 2026 | 2.06 Mn |
| Oct 31, 2025 | 2.07 Mn |
| Jul 31, 2025 | 3.15 Mn |
| Apr 30, 2025 | 2.33 Mn |
| Jan 31, 2025 | 2.16 Mn |
| Oct 31, 2024 | 2.44 Mn |
| Jul 31, 2024 | 2.08 Mn |
| Apr 30, 2024 | 2.41 Mn |
| Jan 31, 2024 | 2.16 Mn |
| Oct 31, 2023 | 2.52 Mn |
| Jul 31, 2023 | 2.51 Mn |
| Apr 30, 2023 | 2.65 Mn |
| Jan 31, 2023 | 3.14 Mn |
| Oct 31, 2022 | 4.36 Mn |
| Jul 31, 2022 | 4.27 Mn |
| Apr 30, 2022 | 2.87 Mn |
| Jan 31, 2022 | 3.09 Mn |
| Oct 31, 2021 | 2.51 Mn |
| Jul 31, 2021 | 2.62 Mn |
API Access
Zeo ScientifiX 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=ZEOX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ZEOX", "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=ZEOX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();