Datavault AI (DVLT) Finished Goods (2017 - 2026)
Datavault AI (DVLT) reported Finished Goods of $486,000 for Q1 2026, down 42.5% from $845,000 a year earlier but up 10.5% from the prior quarter.
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Analysis
Datavault AI (DVLT) Finished Goods (2017 - 2026) Analysis & Trends
At the end of FY2025, Datavault AI posted Finished Goods of $440,000, down 59.6% from FY2024.
- Finished Goods has declined for three consecutive years, with a five-year compound annual growth rate of -4.5% (FY2020 to FY2025).
- By year, Finished Goods came in at $1.09 million in FY2024 (-48.5%), $2.12 million in FY2023 (-47.3%), $4.01 million in FY2022 (+204.1%) and $1.32 million in FY2021 (+138.7%).
- Five-year quarterly Finished Goods spans a low of $440,000 in Q4 2025 and a high of $4.01 million in Q4 2022.
- Year over year, Finished Goods has now declined in each of the last 12 quarters, with an average decline of 47.4% over the last eight quarters.
- The high point for year-over-year Finished Goods in five years was Q4 2022 (growth of 204.1%); the low point was Q4 2025 (a decline of 59.6%).
- Per Business Quant data, the three quarters before Q1 2026 came in at $440,000 (Q4 2025), $659,000 (Q3 2025) and $930,000 (Q2 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Palo Alto Networks | 319.55 Bn | 304.63 Bn | 2.30 Bn |
| 2 | CrowdStrike Holdings | 265.46 Bn | 245.90 Bn | 1.10 Bn |
| 3 | Fortinet | 129.36 Bn | 115.29 Bn | 1.64 Bn |
| 4 | Snowflake | 115.65 Bn | 102.97 Bn | 1.04 Bn |
| 5 | Datadog | 96.45 Bn | 78.09 Bn | 881.34 Mn |
| 6 | Axon Enterprise | 34.50 Bn | 29.03 Bn | 546.45 Mn |
| 7 | Okta | 33.79 Bn | 23.89 Bn | 641.00 Mn |
| 8 | Zscaler | 32.51 Bn | 18.63 Bn | - |
| 9 | Baidu | 29.59 Bn | -44.04 Bn | 1.47 Mn |
| 10 | Datavault AI | 136.71 Mn | 136.71 Mn | 2.88 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Mar 31, 2026 | 486,000.00 |
| Dec 31, 2025 | 440,000.00 |
| Sep 30, 2025 | 659,000.00 |
| Jun 30, 2025 | 930,000.00 |
| Mar 31, 2025 | 845,000.00 |
| Dec 31, 2024 | 1.09 Mn |
| Sep 30, 2024 | 1.24 Mn |
| Jun 30, 2024 | 1.66 Mn |
| Mar 31, 2024 | 1.97 Mn |
| Dec 31, 2023 | 2.12 Mn |
| Sep 30, 2023 | 2.51 Mn |
| Jun 30, 2023 | 2.36 Mn |
| Mar 31, 2023 | 3.76 Mn |
| Dec 31, 2022 | 4.01 Mn |
| Sep 30, 2022 | 3.72 Mn |
| Jun 30, 2022 | 3.84 Mn |
| Mar 31, 2022 | 3.13 Mn |
| Dec 31, 2021 | 1.32 Mn |
| Sep 30, 2021 | 1.72 Mn |
| Jun 30, 2021 | 1.46 Mn |
API Access
Datavault AI Finished Goods 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=finished-goods&ticker=DVLT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "finished-goods", "ticker": "DVLT", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=finished-goods&ticker=DVLT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();