MBody AI (MBAI) Accumulated Expenses (2018 - 2025)
MBody AI's Accumulated Expenses came in at $260,000 for the quarter ended Dec 31, 2025, down 10.3% from $290,000 a year earlier.
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Analysis
MBody AI (MBAI) Accumulated Expenses (2018 - 2025) Analysis & Trends
Going back to the quarter ended Dec 31, 2018, MBody AI's Accumulated Expenses data covers 5 quarters.
- Accumulated Expenses carries a four-year compound annual growth rate of -50.3% (years ended Dec 2021 to Dec 2025).
- Going back by year, Accumulated Expenses was $290,000 in the year ended Dec 31, 2024, -$56,000 in the year ended Dec 31, 2022 and $4.28 million in the year ended Dec 31, 2021.
- The figure for the quarter ended Dec 31, 2025 represents the lowest quarterly Accumulated Expenses since the quarter ended Dec 31, 2022.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 241.25 Bn | 220.40 Bn | 4.88 Bn |
| 2 | Abbott Laboratories | 167.33 Bn | 138.41 Bn | 7.27 Bn |
| 3 | Danaher | 148.83 Bn | 132.65 Bn | 3.61 Bn |
| 4 | Intuitive Surgical | 142.00 Bn | 121.55 Bn | 1.96 Bn |
| 5 | Medtronic | 110.70 Bn | 76.57 Bn | 6.34 Bn |
| 6 | Stryker | 104.72 Bn | 90.84 Bn | 4.50 Bn |
| 7 | Boston Scientific | 62.66 Bn | 57.67 Bn | 3.85 Bn |
| 8 | Edwards Lifesciences | 49.13 Bn | 33.24 Bn | 1.35 Bn |
| 9 | Becton Dickinson | 48.51 Bn | 45.66 Bn | 2.32 Bn |
| 10 | MBody AI | 3.13 Mn | 2.91 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2025 | 260,000.00 |
| Dec 31, 2024 | 290,000.00 |
| Dec 31, 2022 | -56,000.00 |
| Dec 31, 2021 | 4.28 Mn |
| Dec 31, 2018 | -15,000.00 |
API Access
MBody AI 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=MBAI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "MBAI", "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=MBAI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();