Spectral AI (MDAI) Total Liabilities (2020 - 2026)
Spectral AI (MDAI) posted Total Liabilities of $31.49 million for Q2 2026, up 25.2% from $25.16 million a year earlier and up 18.6% from the prior quarter.
Powered by 
Analysis
Spectral AI (MDAI) Total Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, Spectral AI's Total Liabilities came in at $27.13 million, up 40.2% from FY2024.
- Annual Total Liabilities has increased for three consecutive years, with a five-year compound annual growth rate of 186.5% (FY2020 to FY2025).
- In prior years, Spectral AI's Total Liabilities was $19.35 million in FY2024 (+50.7%), $12.84 million in FY2023 (+91.1%), $6.72 million in FY2022 (-97.2%) and $240.36 million in FY2021.
- The Q2 2026 figure stands as the highest quarterly Total Liabilities since Q3 2022.
- On a year-over-year basis, Total Liabilities has increased in each of the last eight quarters, with growth averaging 36.1% over the last eight quarters.
- The strongest year-over-year quarter for Total Liabilities in the past five years was Q4 2023, with growth of 91.1%; the weakest was Q4 2022, with a decline of 97.2%.
- According to Business Quant data, Total Liabilities for the three prior quarters was $26.54 million (Q1 2026), $27.13 million (Q4 2025) and $23.5 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 250.84 Bn | 229.99 Bn | 4.88 Bn | 60.49 Bn |
| 2 | Abbott Laboratories | 174.73 Bn | 145.82 Bn | 7.27 Bn | 57.45 Bn |
| 3 | Danaher | 159.85 Bn | 143.67 Bn | 3.61 Bn | 39.78 Bn |
| 4 | Intuitive Surgical | 146.79 Bn | 126.35 Bn | 1.96 Bn | 2.58 Bn |
| 5 | Medtronic | 114.54 Bn | 80.41 Bn | 6.34 Bn | 42.46 Bn |
| 6 | Stryker | 105.67 Bn | 91.79 Bn | 4.50 Bn | 23.94 Bn |
| 7 | Boston Scientific | 63.93 Bn | 58.94 Bn | 3.85 Bn | 20.04 Bn |
| 8 | Becton Dickinson | 50.12 Bn | 47.27 Bn | 2.32 Bn | 26.32 Bn |
| 9 | Edwards Lifesciences | 50.06 Bn | 34.17 Bn | 1.35 Bn | 3.14 Bn |
| 10 | Spectral AI | 51.82 Mn | 217,734.54 | 1.11 Mn | 31.49 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 31.49 Mn |
| Mar 31, 2026 | 26.54 Mn |
| Dec 31, 2025 | 27.13 Mn |
| Sep 30, 2025 | 23.50 Mn |
| Jun 30, 2025 | 25.16 Mn |
| Mar 31, 2025 | 22.35 Mn |
| Dec 31, 2024 | 19.35 Mn |
| Sep 30, 2024 | 16.38 Mn |
| Jun 30, 2024 | 18.60 Mn |
| Mar 31, 2024 | 17.95 Mn |
| Dec 31, 2023 | 12.84 Mn |
| Sep 30, 2023 | 10.88 Mn |
| Jun 30, 2023 | -717,872.00 |
| Mar 31, 2023 | -3.28 Mn |
| Dec 31, 2022 | 6.72 Mn |
| Sep 30, 2022 | 241.41 Mn |
| Jun 30, 2022 | 240.29 Mn |
| Mar 31, 2022 | 240.18 Mn |
| Dec 31, 2021 | 240.36 Mn |
| Sep 30, 2021 | 270.42 Mn |
API Access
Spectral AI Total Liabilities 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=total-liabilities&ticker=MDAI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "MDAI", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=total-liabilities&ticker=MDAI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();