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Substrate Artificial Inteligence (XMAD:SAI) Debt-to-Revenue : 0.26 (As of Dec. 2023)


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What is Substrate Artificial Inteligence Debt-to-Revenue?

Debt-to-Revenue measures a company's ability to pay off its debt.

Substrate Artificial Inteligence's Short-Term Debt & Capital Lease Obligation for the quarter that ended in Dec. 2023 was €0.29 Mil. Substrate Artificial Inteligence's Long-Term Debt & Capital Lease Obligation for the quarter that ended in Dec. 2023 was €3.30 Mil. Substrate Artificial Inteligence's annualized Revenue for the quarter that ended in Dec. 2023 was €13.62 Mil. Substrate Artificial Inteligence's annualized Debt-to-Revenue for the quarter that ended in Dec. 2023 was 0.26.


Substrate Artificial Inteligence Debt-to-Revenue Historical Data

The historical data trend for Substrate Artificial Inteligence's Debt-to-Revenue can be seen below:

* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.

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Substrate Artificial Inteligence Debt-to-Revenue Chart

Substrate Artificial Inteligence Annual Data
Trend Dec21 Dec22 Dec23
Debt-to-Revenue
0.01 0.37 0.42

Substrate Artificial Inteligence Semi-Annual Data
Jun21 Dec21 Jun22 Dec22 Jun23 Dec23
Debt-to-Revenue Get a 7-Day Free Trial 0.01 0.29 0.31 0.44 0.26

Competitive Comparison of Substrate Artificial Inteligence's Debt-to-Revenue

For the Software - Infrastructure subindustry, Substrate Artificial Inteligence's Debt-to-Revenue, along with its competitors' market caps and Debt-to-Revenue data, can be viewed below:

* Competitive companies are chosen from companies within the same industry, with headquarter located in same country, with closest market capitalization; x-axis shows the market cap, and y-axis shows the term value; the bigger the dot, the larger the market cap. Note that "N/A" values will not show up in the chart.


Substrate Artificial Inteligence's Debt-to-Revenue Distribution in the Software Industry

For the Software industry and Technology sector, Substrate Artificial Inteligence's Debt-to-Revenue distribution charts can be found below:

* The bar in red indicates where Substrate Artificial Inteligence's Debt-to-Revenue falls into.



Substrate Artificial Inteligence Debt-to-Revenue Calculation

Debt-to-Revenue measures a company's ability to pay off its debt.

Substrate Artificial Inteligence's Debt-to-Revenue for the fiscal year that ended in Dec. 2023 is calculated as

Debt-to-Revenue=Total Debt / Revenue
=(Short-Term Debt & Capital Lease Obligation + Long-Term Debt & Capital Lease Obligation) / Revenue
=(0.29 + 3.3) / 8.609
=0.42

Substrate Artificial Inteligence's annualized Debt-to-Revenue for the quarter that ended in Dec. 2023 is calculated as

Debt-to-Revenue=Total Debt / Revenue
=(Short-Term Debt & Capital Lease Obligation + Long-Term Debt & Capital Lease Obligation) / Revenue
=(0.29 + 3.3) / 13.622
=0.26

* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.

In the calculation of annual Debt-to-Revenue, the Revenue of the last fiscal year is used. In calculating the annualized quarterly data, the Revenue data used here is two times the quarterly (Dec. 2023) Revenue data.


Substrate Artificial Inteligence Debt-to-Revenue Related Terms

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Substrate Artificial Inteligence Business Description

Traded in Other Exchanges
Address
C/ Maria de Molina, 41, Office 506, Madrid, ESP, 28006
Substrate Artificial Inteligence SA is an Artificial Intelligence company in Spain. Its software is applied in agritech, energy, industry, fintech, human resources, or health sectors. Its technology is easy to implement and allows it to address all the problems faced by companies in the digitization and streamlining of their processes, optimizing decision-making and generating great cost savings.

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