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iLearningEngines (iLearningEngines) Total Long-Term Assets : $23.5 Mil (As of Jun. 2023)


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What is iLearningEngines Total Long-Term Assets?

Total Long-Term Assets includes Investments And Advances, Intangible Assets, Property, Plant and Equipment and Other Long Term Assets. iLearningEngines's Total Long-Term Assets for the quarter that ended in Jun. 2023 was $23.5 Mil.


iLearningEngines Total Long-Term Assets Historical Data

The historical data trend for iLearningEngines's Total Long-Term Assets 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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iLearningEngines Total Long-Term Assets Chart

iLearningEngines Annual Data
Trend Dec20 Dec21 Dec22
Total Long-Term Assets
- 1.36 18.50

iLearningEngines Semi-Annual Data
Dec20 Dec21 Jun22 Dec22 Jun23
Total Long-Term Assets - 1.36 - 18.50 23.47

iLearningEngines Total Long-Term Assets Calculation

Total Long-Term Assets are the sum of the carrying amounts of all assets that are expected to be realized in cash, sold or consumed longer than one year. It includes Investments And Advances, Intangible Assets, Property, Plant and Equipment and Other Long Term Assets.


iLearningEngines Total Long-Term Assets Related Terms

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iLearningEngines (iLearningEngines) Business Description

Comparable Companies
Traded in Other Exchanges
N/A
Address
6701 Democracy Boulevard, Suite 300, Bethesda, MD, USA, 20817
iLearningEngines Inc is an AI and automation platform that empowers its customers to productize their institutional knowledge by transforming it into actionable intellectual property that enhances outcomes for employees, customers and other stakeholders. Its platform enables enterprises to build intelligent Knowledge Clouds that incorporate large volumes of structured and unstructured information across disparate internal and external systems and to automate organizational processes that leverage these Knowledge Clouds to improve performance. The company combines its offerings with vertically focused capabilities and data models to operationalize AI and automation to effectively and efficiently address critical challenges facing its customers.