Exousia Bio (LMMY) Accumulated Expenses (2023 - 2024)
Exousia Bio's Accumulated Expenses came in at $1,211 for fiscal Q1 2025 (quarter ended Aug 31, 2024), up 5.8% from $1,145 a year earlier and unchanged from the prior quarter.
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Analysis
Exousia Bio (LMMY) Accumulated Expenses (2023 - 2024) Analysis & Trends
Going back to fiscal Q4 2023, Exousia Bio's Accumulated Expenses data covers 6 quarters.
- Going back by fiscal year, Accumulated Expenses was $610.00 in FY2023.
- The five-year range for quarterly Accumulated Expenses is $610.00 (fiscal Q4 2023) to $3,980 (fiscal Q3 2024).
- Business Quant data shows LMMY's Accumulated Expenses at $1,211 (Q4 2024), $3,980 (Q3 2024) and $2,069 (Q2 2024) in the three fiscal quarters before Q1 2025.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Bryn | 945.00 Bn | 945.00 Bn | - |
| 2 | Veeva Systems | 44.24 Bn | 16.49 Bn | 695.95 Mn |
| 3 | Samsara | 24.06 Bn | 20.83 Bn | 392.58 Mn |
| 4 | Toast | 17.18 Bn | 9.85 Bn | 516.00 Mn |
| 5 | Ptc | 15.95 Bn | 14.76 Bn | 490.47 Mn |
| 6 | Duolingo | 13.49 Bn | 8.67 Bn | 216.74 Mn |
| 7 | Trimble | 13.41 Bn | 12.48 Bn | 674.90 Mn |
| 8 | Manhattan Associates | 11.90 Bn | 10.90 Bn | 168.33 Mn |
| 9 | Costar | 11.09 Bn | 5.06 Bn | 728.00 Mn |
| 10 | Exousia Bio | 335,295.33 | 335,295.33 | -62,108.00 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 31, 2024 | 1,211.00 |
| May 31, 2024 | 1,211.00 |
| Feb 29, 2024 | 3,980.00 |
| Nov 30, 2023 | 2,069.00 |
| Aug 31, 2023 | 1,145.00 |
| May 31, 2023 | 610.00 |
API Access
Exousia Bio Accumulated 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=accumulated-expenses&ticker=LMMY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "LMMY", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=LMMY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();