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iLearningEngines (iLearningEngines) Capex-to-Operating-Income : 0.00 (As of Jun. 2023)


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What is iLearningEngines Capex-to-Operating-Income?

Capex-to-Operating-Income measures a company's investments in physical assets such as property, industrial buildings or equipment to its operating income.

iLearningEngines's Capital Expenditure for the six months ended in Jun. 2023 was $-0.01 Mil. Its Operating Income for the six months ended in Jun. 2023 was $6.10 Mil.

Hence, iLearningEngines's Capex-to-Operating-Income for the six months ended in Jun. 2023 was 0.00.

iLearningEngines Capex-to-Operating-Income Historical Data

The historical data trend for iLearningEngines's Capex-to-Operating-Income 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 Capex-to-Operating-Income Chart

iLearningEngines Annual Data
Trend Dec20 Dec21 Dec22
Capex-to-Operating-Income
- - -

iLearningEngines Semi-Annual Data
Dec20 Dec21 Jun22 Dec22 Jun23
Capex-to-Operating-Income - - - - -

Competitive Comparison of iLearningEngines's Capex-to-Operating-Income

For the Software - Infrastructure subindustry, iLearningEngines's Capex-to-Operating-Income, along with its competitors' market caps and Capex-to-Operating-Income 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.

iLearningEngines's Capex-to-Operating-Income Distribution in the Software Industry

For the Software industry and Technology sector, iLearningEngines's Capex-to-Operating-Income distribution charts can be found below:

* The bar in red indicates where iLearningEngines's Capex-to-Operating-Income falls into.


iLearningEngines Capex-to-Operating-Income Calculation

iLearningEngines's Capex-to-Operating-Income for the fiscal year that ended in Dec. 2022 is calculated as

Capex-to-Operating-Income=- Capital Expenditure / Operating Income
=- (0) / 11.878
=0.00

iLearningEngines's Capex-to-Operating-Income for the quarter that ended in Jun. 2023 is calculated as

Capex-to-Operating-Income=- Capital Expenditure / Operating Income
=- (-0.007) / 6.099
=0.00

* 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.

iLearningEngines  (NAS:AILE) Capex-to-Operating-Income Explanation

Capex-to-Operating-Income assesses how much emphasis a company is placing upon investing in capital-intensive projects. The ratio is generally a good gauge to quantify how much focus on growth a company has. Typically, smaller companies that are still growing and expanding will have a higher Capex to Operating Income Ratio, since such businesses are likely investing more in physical assets. Lower ratios could indicate that a company has reached maturity and it is no longer pursuing aggressive growth.

iLearningEngines Capex-to-Operating-Income Related Terms

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iLearningEngines (iLearningEngines) Business Description

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Address
6701 Democracy Boulevard, Suite 300, Bethesda, MD, USA, 20817
Website
https://www.ilearningengines.com
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.