Audioeye (AEYE) Operating Expenses (2012 - 2026)
Audioeye's Operating Expenses came in at $9.05 million for Q2 2026, up 22.6% from $7.38 million a year earlier but down 10.7% from the prior quarter.
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Analysis
Audioeye (AEYE) Operating Expenses (2012 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Audioeye reported Operating Expenses of $36.51 million, up 9.9% year-over-year; for FY2025, it came in at $33.39 million, up 6.6% from FY2024.
- Operating Expenses carries a five-year compound annual growth rate of 9.1% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $31.33 million in FY2024 (+3.4%), $30.31 million in FY2023 (-8.5%), $33.12 million in FY2022 (-2.3%) and $33.9 million in FY2021 (+56.6%).
- The five-year range for quarterly Operating Expenses is $6.67 million (Q4 2023) to $10.14 million (Q1 2026).
- Year-over-year, Operating Expenses has increased for eight consecutive quarters, with growth averaging 14.2% over the last eight quarters.
- The fastest year-over-year change in Operating Expenses over five years came in Q3 2021 (growth of 71.1%), and the weakest in Q4 2022 (a decline of 19.3%).
- Business Quant data shows AEYE's Operating Expenses at $10.14 million (Q1 2026), $9.1 million (Q4 2025) and $8.23 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 450.50 Bn | 419.56 Bn | 1.64 Bn | 726.59 Mn |
| 2 | Oracle | 401.01 Bn | 273.57 Bn | - | 12.62 Bn |
| 3 | Sap Se | 257.03 Bn | 178.11 Bn | 8.40 Bn | -8.41 Bn |
| 4 | Salesforce | 187.04 Bn | 142.92 Bn | 8.70 Bn | 6.37 Bn |
| 5 | ServiceNow | 135.91 Bn | 114.37 Bn | 2.82 Bn | 2.66 Bn |
| 6 | Automatic Data Processing | 104.14 Bn | 86.27 Bn | 2.51 Bn | 4.34 Bn |
| 7 | Intuit | 72.30 Bn | 51.65 Bn | 3.44 Bn | 3.88 Bn |
| 8 | Relx | 60.17 Bn | 57.14 Bn | - | - |
| 9 | Strategy | 55.31 Bn | 48.30 Bn | 81.55 Mn | 8.41 Bn |
| 10 | Audioeye | 85.16 Mn | 58.05 Mn | 8.45 Mn | 9.05 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 9.05 Mn |
| Mar 31, 2026 | 10.14 Mn |
| Dec 31, 2025 | 9.10 Mn |
| Sep 30, 2025 | 8.23 Mn |
| Jun 30, 2025 | 7.38 Mn |
| Mar 31, 2025 | 8.68 Mn |
| Dec 31, 2024 | 9.08 Mn |
| Sep 30, 2024 | 8.09 Mn |
| Jun 30, 2024 | 7.20 Mn |
| Mar 31, 2024 | 6.95 Mn |
| Dec 31, 2023 | 6.67 Mn |
| Sep 30, 2023 | 7.44 Mn |
| Jun 30, 2023 | 8.08 Mn |
| Mar 31, 2023 | 8.12 Mn |
| Dec 31, 2022 | 7.92 Mn |
| Sep 30, 2022 | 8.06 Mn |
| Jun 30, 2022 | 8.34 Mn |
| Mar 31, 2022 | 8.81 Mn |
| Dec 31, 2021 | 9.81 Mn |
| Sep 30, 2021 | 9.29 Mn |
API Access
Audioeye 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=AEYE&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "AEYE", "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=AEYE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();