Zapata Computing Holdings (Zapata Computing Holdings) Debt-to-Revenue : 1.67 (As of Dec. 2023)

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What is Zapata Computing Holdings Debt-to-Revenue?

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

Zapata Computing Holdings's Short-Term Debt & Capital Lease Obligation for the quarter that ended in Dec. 2023 was $0.25 Mil. Zapata Computing Holdings's Long-Term Debt & Capital Lease Obligation for the quarter that ended in Dec. 2023 was $8.90 Mil. Zapata Computing Holdings's annualized Revenue for the quarter that ended in Dec. 2023 was $5.48 Mil. Zapata Computing Holdings's annualized Debt-to-Revenue for the quarter that ended in Dec. 2023 was 1.67.

Zapata Computing Holdings Debt-to-Revenue Historical Data

The historical data trend for Zapata Computing Holdings'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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Zapata Computing Holdings Debt-to-Revenue Chart

Zapata Computing Holdings Annual Data

Trend

Dec21

Dec22

Dec23

Debt-to-Revenue

0.12

1.61

Zapata Computing Holdings Semi-Annual Data
	Dec21	Jun22	Dec22	Jun23	Dec23
Debt-to-Revenue	N/A	-	0.11	1.00	1.67

Competitive Comparison of Zapata Computing Holdings's Debt-to-Revenue

For the Software - Infrastructure subindustry, Zapata Computing Holdings'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.

Zapata Computing Holdings's Debt-to-Revenue Distribution in the Software Industry

For the Software industry and Technology sector, Zapata Computing Holdings's Debt-to-Revenue distribution charts can be found below:

* The bar in red indicates where Zapata Computing Holdings's Debt-to-Revenue falls into.

Zapata Computing Holdings Debt-to-Revenue Calculation

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

Zapata Computing Holdings'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
	=	(0.252	+	8.9)	/	5.683
	=	1.61

Zapata Computing Holdings'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
	=	(0.252	+	8.9)	/	5.478
	=	1.67

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.

Zapata Computing Holdings Debt-to-Revenue Related Terms

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Zapata Computing Holdings (Zapata Computing Holdings) Business Description

Industry

GURUFOCUS.COM » STOCK LIST » Technology » Software » Zapata Computing Holdings Inc (NAS:ZPTA) » Definitions » Debt-to-Revenue

Comparable Companies

Traded in Other Exchanges

N/A

Address

100 Federal Street, Floor 20, Boston, MA, USA, 02110

Website

https://www.zapata.ai

Zapata Computing Holdings Inc is an Industrial Generative AI software company that develops generative AI applications and provides accompanying services to solve complex industrial problems. Its computational approaches leverage the statistical advantages of math based on quantum physics. Its primary target customers are enterprise organizations. It offers subscription-based solutions that combine software and services to develop custom Industrial Generative AI applications designed to resolve its enterprise customers' specific problems.

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