iCetana (ASX:ICE) Long-Term Debt : A$0.00 Mil (As of Dec. 2023)

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What is iCetana Long-Term Debt?

iCetana's Long-Term Debt for the quarter that ended in Dec. 2023 was A$0.00 Mil.

iCetana Long-Term Debt Historical Data

The historical data trend for iCetana's Long-Term Debt 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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iCetana Long-Term Debt Chart

iCetana Annual Data

Trend

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Long-Term Debt

iCetana Semi-Annual Data
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iCetana (ASX:ICE) Long-Term Debt Explanation

Long-Term Debt is the sum of the carrying values as of the balance sheet date of all long-term debt, which is debt initially having maturities due after one year or beyond the operating cycle, if longer, but excluding the portions thereof scheduled to be repaid within one year or the normal operating cycle, if longer. Long-Term Debt includes notes payable, bonds payable, mortgage loans, convertible debt, subordinated debt and other types of long term debt.

iCetana Long-Term Debt Related Terms

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iCetana (ASX:ICE) Business Description

Industry

GURUFOCUS.COM » STOCK LIST » Technology » Software » iCetana Ltd (ASX:ICE) » Definitions » Long-Term Debt

Comparable Companies

Traded in Other Exchanges

N/A

Address

152 St Georges Terrace, Level 32, Perth, WA, AUS, 6000

Website

https://www.icetana.com.au

iCetana Ltd is an AI-assisted video surveillance solution software company. It provides video analytics solutions for large scale surveillance networks. Its software integrates existing video management systems and IP cameras. Its geographical segments are Asia Pacific (APAC); North America (NA) and Europe, Middle East & Africa (EMEA). Its product includes iCetana AI video surveillance software which is an AI-driven video analytics surveillance solution designed to automatically identify anomalous events in real-time.