Innodata (INOD) Accumulated Expenses (2010 - 2026)
Innodata (INOD) posted Accumulated Expenses of $36.3 million for Q2 2026, up 33.72% on a QoQ basis from $27.2 million in Q1 2026, and up 193.66% year-over-year from $12.4 million in Q2 2025.
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Analysis
Innodata (INOD) Accumulated Expenses (2010 - 2026) Analysis & Trends
Innodata has reported Accumulated Expenses for 17 years, with the latest figure at $36.3 million in Q2 2026.
- On a quarterly basis, Accumulated Expenses rose 193.66% year-over-year to $36.3 million in Q2 2026; TTM through Jun 2026 was $36.3 million, a 193.66% increase from a year earlier, with the FY2025 full-year figure at $16.5 million, up 19.11% from the prior year.
- Accumulated Expenses was $36.3 million for Q2 2026 at Innodata, up from $27.2 million in the prior quarter.
- The five-year high for Accumulated Expenses was $36.3 million in Q2 2026, with the low at $6.4 million in Q2 2022.
- Average Accumulated Expenses over 5 years is $12.0 million, with a median of $8.0 million recorded in 2023.
- The sharpest annual moves came in 2022 and 2026: Accumulated Expenses decreased 11.95% in 2022, then soared 193.66% in 2026.
- Over 5 years, Accumulated Expenses stood at $7.2 million in 2022, then rose by 7.57% to $7.8 million in 2023, then jumped by 77.41% to $13.8 million in 2024, then grew by 19.11% to $16.5 million in 2025, then soared by 120.55% to $36.3 million in 2026.
- The last three Accumulated Expenses figures came in at $36.3 million (Q2 2026), $27.2 million (Q1 2026), and $16.5 million (Q4 2025), per Business Quant data.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Infosys | 44.17 Bn | 44.22 Bn | 1.60 Bn |
| 2 | Cognizant Technology Solutions | 26.84 Bn | 25.79 Bn | 1.83 Bn |
| 3 | Cgi | 13.60 Bn | 13.02 Bn | - |
| 4 | EPAM Systems | 5.82 Bn | 5.04 Bn | 429.57 Mn |
| 5 | Science Applications International | 5.60 Bn | 5.47 Bn | 239.00 Mn |
| 6 | ExlService Holdings | 5.35 Bn | 5.07 Bn | 225.96 Mn |
| 7 | Kyndryl Holdings | 2.65 Bn | 639.03 Mn | 776.00 Mn |
| 8 | Innodata | 2.10 Bn | 1.85 Bn | 42.46 Mn |
| 9 | Formula Systems (1985) | 1.83 Bn | 1.41 Bn | 158.43 Mn |
| 10 | DXC Technology | 1.74 Bn | 9.39 Mn | 611.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 36.35 Mn |
| Mar 31, 2026 | 27.18 Mn |
| Dec 31, 2025 | 16.48 Mn |
| Sep 30, 2025 | 15.26 Mn |
| Jun 30, 2025 | 12.38 Mn |
| Mar 31, 2025 | 13.61 Mn |
| Dec 31, 2024 | 13.84 Mn |
| Sep 30, 2024 | 9.62 Mn |
| Jun 30, 2024 | 6.64 Mn |
| Mar 31, 2024 | 7.30 Mn |
| Dec 31, 2023 | 7.80 Mn |
| Sep 30, 2023 | 8.12 Mn |
| Jun 30, 2023 | 6.80 Mn |
| Mar 31, 2023 | 6.84 Mn |
| Dec 31, 2022 | 7.25 Mn |
| Sep 30, 2022 | 6.91 Mn |
| Jun 30, 2022 | 6.40 Mn |
| Mar 31, 2022 | 7.23 Mn |
| Dec 31, 2021 | 7.56 Mn |
| Sep 30, 2021 | 6.69 Mn |
API Access
Innodata 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=INOD&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "INOD", "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=INOD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();