Palladyne AI (PDYN) Accumulated Expenses (2020 - 2026)
Palladyne AI (PDYN) posted Accumulated Expenses of $5.87 million for Q2 2026, up 127.8% from $2.58 million a year earlier and up 37.3% from the prior quarter.
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Analysis
Palladyne AI (PDYN) Accumulated Expenses (2020 - 2026) Analysis & Trends
At the end of FY2025, Palladyne AI's Accumulated Expenses came in at $3.55 million, up 21.6% from FY2024.
- Annual Accumulated Expenses shows a five-year compound annual growth rate of 23.1% (FY2020 to FY2025).
- In prior years, Palladyne AI's Accumulated Expenses was $2.92 million in FY2024 (-49.7%), $5.81 million in FY2023 (-3.7%), $6.03 million in FY2022 (+34.5%) and $4.48 million in FY2021 (+257.0%).
- The Q2 2026 figure stands as the highest quarterly Accumulated Expenses since Q4 2022.
- On a year-over-year basis, Accumulated Expenses has increased in each of the last three quarters, with growth averaging 16.8% over the last eight quarters.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was Q4 2021, with growth of 257.0%; the weakest was Q2 2023, with a decline of 50.2%.
- According to Business Quant data, Accumulated Expenses for the three prior quarters was $4.27 million (Q1 2026), $3.55 million (Q4 2025) and $2.92 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Aurora Innovation | 11.07 Bn | 6.10 Bn | -5.00 Mn |
| 2 | Mobileye Global | 6.05 Bn | -61.98 Mn | 235.00 Mn |
| 3 | Pony AI | 2.84 Bn | 2.91 Bn | 6.35 Mn |
| 4 | WeRide | 1.82 Bn | -1.20 Bn | 12.76 Mn |
| 5 | Securetech Innovations | 781.01 Mn | 780.42 Mn | - |
| 6 | Serve Robotics | 402.21 Mn | 402.21 Mn | -8.78 Mn |
| 7 | Kodiak AI | 372.81 Mn | -135.31 Mn | - |
| 8 | Richtech Robotics | 354.53 Mn | 354.53 Mn | 802,000.00 |
| 9 | ECARX Holdings | 326.03 Mn | -35.79 Mn | 44.50 Mn |
| 10 | Palladyne AI | 253.58 Mn | 61.95 Mn | 1.68 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 5.87 Mn |
| Mar 31, 2026 | 4.27 Mn |
| Dec 31, 2025 | 3.55 Mn |
| Sep 30, 2025 | 2.92 Mn |
| Jun 30, 2025 | 2.58 Mn |
| Mar 31, 2025 | 1.87 Mn |
| Dec 31, 2024 | 2.92 Mn |
| Sep 30, 2024 | 3.55 Mn |
| Jun 30, 2024 | 2.99 Mn |
| Mar 31, 2024 | 3.09 Mn |
| Dec 31, 2023 | 5.81 Mn |
| Sep 30, 2023 | 4.58 Mn |
| Jun 30, 2023 | 4.05 Mn |
| Mar 31, 2023 | 5.86 Mn |
| Dec 31, 2022 | 6.03 Mn |
| Sep 30, 2022 | 7.23 Mn |
| Jun 30, 2022 | 8.13 Mn |
| Mar 31, 2022 | 3.87 Mn |
| Dec 31, 2021 | 4.48 Mn |
| Sep 30, 2021 | 2.69 Mn |
API Access
Palladyne 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=PDYN&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "PDYN", "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=PDYN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();