Fabric.AI (FABC) Operating Expenses (2010 - 2026)
Fabric.AI's Operating Expenses came in at $3.33 million for Q2 2026, up 114.9% from $1.55 million a year earlier and up 95.7% from the prior quarter.
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Analysis
Fabric.AI (FABC) Operating Expenses (2010 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Fabric.AI reported Operating Expenses of $11.01 million, up 17.9% year-over-year; for FY2025, it came in at $9.5 million, down 25.7% from FY2024.
- Operating Expenses carries a five-year compound annual growth rate of -0.9% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $12.79 million in FY2024 (-45.6%), $23.52 million in FY2023 (+16.3%), $20.22 million in FY2022 (-34.8%) and $31.04 million in FY2021 (+212.3%).
- The Q2 2026 figure represents the highest quarterly Operating Expenses since Q4 2024.
- Year-over-year, Operating Expenses increased in two of the last eight quarters, with an average decline of 6.2%.
- The fastest year-over-year change in Operating Expenses over five years came in Q3 2021 (growth of 374.0%), and the weakest in Q3 2024 (a decline of 73.0%).
- Business Quant data shows FABC's Operating Expenses at $1.7 million (Q1 2026), $3.16 million (Q4 2025) and $2.82 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 | Robinhood Markets | 104.70 Bn | 85.79 Bn | - | 734.00 Mn |
| 2 | Bank of New York Mellon | 100.72 Bn | 40.09 Bn | - | 3.44 Bn |
| 3 | Cme | 94.58 Bn | 94.58 Bn | - | 599.10 Mn |
| 4 | Intercontinental Exchange | 85.83 Bn | 79.63 Bn | - | 1.28 Bn |
| 5 | Nasdaq | 52.05 Bn | 49.49 Bn | 1.50 Bn | 788.00 Mn |
| 6 | State Street | 49.39 Bn | 49.39 Bn | - | 2.66 Bn |
| 7 | Interactive Brokers | 39.24 Bn | 32.69 Bn | - | 440.00 Mn |
| 8 | Northern Trust | 31.94 Bn | 31.94 Bn | - | 1.64 Bn |
| 9 | Cboe Global Markets | 26.47 Bn | 18.13 Bn | 731.60 Mn | 255.60 Mn |
| 10 | Fabric.AI | 9.77 Mn | -39.10 Mn | - | 3.33 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 3.33 Mn |
| Mar 31, 2026 | 1.70 Mn |
| Dec 31, 2025 | 3.16 Mn |
| Sep 30, 2025 | 2.82 Mn |
| Jun 30, 2025 | 1.55 Mn |
| Mar 31, 2025 | 1.97 Mn |
| Dec 31, 2024 | 4.17 Mn |
| Sep 30, 2024 | 1.65 Mn |
| Jun 30, 2024 | 2.88 Mn |
| Mar 31, 2024 | 4.09 Mn |
| Dec 31, 2023 | 5.66 Mn |
| Sep 30, 2023 | 6.10 Mn |
| Jun 30, 2023 | 6.07 Mn |
| Mar 31, 2023 | 5.69 Mn |
| Dec 31, 2022 | 6.46 Mn |
| Sep 30, 2022 | 5.22 Mn |
| Jun 30, 2022 | 4.13 Mn |
| Mar 31, 2022 | 4.42 Mn |
| Dec 31, 2021 | 5.86 Mn |
| Sep 30, 2021 | 11.62 Mn |
API Access
Fabric.AI 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=FABC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "FABC", "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=FABC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();