Agilysys (AGYS) Operating Expenses (2010 - 2026)
Agilysys' Operating Expenses was $45.92 million in fiscal Q1 2027 (quarter ended Jun 30, 2026), up 7.4% from $42.77 million a year earlier and up 12.5% from the prior quarter.
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Analysis
Agilysys (AGYS) Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Agilysys' Operating Expenses was $160.05 million through Jun 30, 2026, up 1.3% year-over-year; for FY2026 (ended Mar 31, 2026), it was $156.91 million, up 5.0% from FY2025.
- Operating Expenses has now increased for three consecutive fiscal years, though with a five-year compound annual growth rate of -1.7% (FY2021 to FY2026).
- In earlier fiscal years, Operating Expenses was $149.4 million in FY2025 (+16.3%), $128.5 million in FY2024 (+19.0%), $107.94 million in FY2023 (-25.7%) and $145.34 million in FY2022 (-15.0%).
- The fiscal Q1 2027 figure marks the highest quarterly Operating Expenses since fiscal Q2 2024.
- Compared with a year earlier, Operating Expenses has increased for three straight quarters, with an average decline of 1.0% over the last seven quarters.
- The best year-over-year quarter for Operating Expenses over five years was fiscal Q2 2022 (growth of 36.6%); the worst was fiscal Q4 2022 (a decline of 47.6%).
- Per Business Quant data, AGYS's Operating Expenses in the three fiscal quarters before Q1 2027 was $40.8 million (Q4 2026), $38.51 million (Q3 2026) and $34.82 million (Q2 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Bryn | 945.00 Bn | 945.00 Bn | - | 178,646.00 |
| 2 | Veeva Systems | 45.35 Bn | 17.59 Bn | 695.95 Mn | 420.93 Mn |
| 3 | Samsara | 22.20 Bn | 18.97 Bn | 392.58 Mn | 387.71 Mn |
| 4 | Toast | 17.53 Bn | 10.20 Bn | 516.00 Mn | 364.00 Mn |
| 5 | Ptc | 15.47 Bn | 14.28 Bn | 490.47 Mn | 323.96 Mn |
| 6 | Trimble | 13.41 Bn | 12.48 Bn | 674.90 Mn | 542.90 Mn |
| 7 | Duolingo | 12.56 Bn | 7.73 Bn | 216.74 Mn | 182.80 Mn |
| 8 | Manhattan Associates | 11.77 Bn | 10.77 Bn | 168.33 Mn | 231.56 Mn |
| 9 | Costar | 10.95 Bn | 4.91 Bn | 728.00 Mn | 652.00 Mn |
| 10 | Agilysys | 2.74 Bn | 2.36 Bn | 55.66 Mn | 45.92 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 45.92 Mn |
| Mar 31, 2026 | 40.80 Mn |
| Dec 31, 2025 | 38.51 Mn |
| Sep 30, 2025 | 34.82 Mn |
| Jun 30, 2025 | 42.77 Mn |
| Mar 31, 2025 | 39.74 Mn |
| Dec 31, 2024 | 36.45 Mn |
| Sep 30, 2024 | 39.09 Mn |
| Jun 30, 2024 | 34.12 Mn |
| Mar 31, 2024 | -42.29 Mn |
| Dec 31, 2023 | 45.53 Mn |
| Sep 30, 2023 | 47.33 Mn |
| Jun 30, 2023 | 46.34 Mn |
| Mar 31, 2023 | -34.42 Mn |
| Dec 31, 2022 | 40.15 Mn |
| Sep 30, 2022 | 39.48 Mn |
| Jun 30, 2022 | 37.49 Mn |
| Mar 31, 2022 | 39.40 Mn |
| Dec 31, 2021 | 35.19 Mn |
| Sep 30, 2021 | 35.64 Mn |
API Access
Agilysys 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=AGYS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "AGYS", "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=AGYS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();