Procore Technologies (PCOR) Total Non-Current Liabilities (2020 - 2026)
Procore Technologies (PCOR) reported Total Non-Current Liabilities of $955.16 million for Q2 2026, up 23.2% from $775.48 million a year earlier and up 6.4% from the prior quarter.
Procore Technologies (PCOR) Total Non-Current Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, Procore Technologies posted Total Non-Current Liabilities of $963.01 million, up 19.2% from FY2024.
- Total Non-Current Liabilities has increased for four consecutive years, though with a five-year compound annual growth rate of -2.5% (FY2020 to FY2025).
- By year, Total Non-Current Liabilities came in at $807.9 million in FY2024 (+10.4%), $731.63 million in FY2023 (+17.9%), $620.58 million in FY2022 (+25.0%) and $496.65 million in FY2021 (-54.5%).
- Five-year quarterly Total Non-Current Liabilities spans a low of $411.52 million in Q3 2021 and a high of $963.01 million in Q4 2025.
- Year over year, Total Non-Current Liabilities has now increased in each of the last 17 quarters, with growth averaging 14.7% over the last eight quarters.
- The high point for year-over-year Total Non-Current Liabilities in five years was Q3 2022 (growth of 33.6%); the low point was Q4 2021 (a decline of 54.5%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $897.81 million (Q1 2026), $963.01 million (Q4 2025) and $822.52 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Bryn | 945.00 Bn | 945.00 Bn | - | - |
| 2 | Veeva Systems | 50.52 Bn | 22.77 Bn | 695.95 Mn | 1.60 Bn |
| 3 | Samsara | 24.02 Bn | 20.79 Bn | 392.58 Mn | 1.15 Bn |
| 4 | Ptc | 22.16 Bn | 20.98 Bn | 490.47 Mn | 2.94 Bn |
| 5 | Toast | 18.74 Bn | 11.41 Bn | 516.00 Mn | 1.10 Bn |
| 6 | Trimble | 14.17 Bn | 13.23 Bn | 674.90 Mn | 3.15 Bn |
| 7 | Manhattan Associates | 13.17 Bn | 12.17 Bn | 168.33 Mn | 528.94 Mn |
| 8 | Costar | 12.94 Bn | 6.89 Bn | 728.00 Mn | 2.16 Bn |
| 9 | Bentley Systems | 11.23 Bn | 10.69 Bn | 336.74 Mn | 2.26 Bn |
| 10 | Procore Technologies | 8.77 Bn | 6.07 Bn | 299.80 Mn | 955.16 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 955.16 Mn |
| Mar 31, 2026 | 897.81 Mn |
| Dec 31, 2025 | 963.01 Mn |
| Sep 30, 2025 | 822.52 Mn |
| Jun 30, 2025 | 775.48 Mn |
| Mar 31, 2025 | 755.41 Mn |
| Dec 31, 2024 | 807.90 Mn |
| Sep 30, 2024 | 727.76 Mn |
| Jun 30, 2024 | 705.96 Mn |
| Mar 31, 2024 | 679.15 Mn |
| Dec 31, 2023 | 731.63 Mn |
| Sep 30, 2023 | 652.68 Mn |
| Jun 30, 2023 | 605.23 Mn |
| Mar 31, 2023 | 602.58 Mn |
| Dec 31, 2022 | 620.58 Mn |
| Sep 30, 2022 | 549.65 Mn |
| Jun 30, 2022 | 512.51 Mn |
| Mar 31, 2022 | 503.55 Mn |
| Dec 31, 2021 | 496.65 Mn |
| Sep 30, 2021 | 411.52 Mn |
Procore Technologies Total Non-Current 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-non-current-liabilities&ticker=PCOR&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "PCOR", "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-non-current-liabilities&ticker=PCOR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();