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iLearningEngines (iLearningEngines) Additional Paid-In Capital : $36.4 Mil(As of Jun. 2023)


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What is iLearningEngines Additional Paid-In Capital?


iLearningEngines's quarterly additional paid-in capital increased from Jun. 2022 ($0.0 Mil) to Dec. 2022 ($36.4 Mil) but then stayed the same from Dec. 2022 ($36.4 Mil) to Jun. 2023 ($36.4 Mil).

iLearningEngines's annual additional paid-in capital increased from Dec. 2020 ($0.0 Mil) to Dec. 2021 ($35.5 Mil) and increased from Dec. 2021 ($35.5 Mil) to Dec. 2022 ($36.4 Mil).


iLearningEngines Additional Paid-In Capital Historical Data

The historical data trend for iLearningEngines's Additional Paid-In Capital 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 Additional Paid-In Capital Chart

iLearningEngines Annual Data
Trend Dec20 Dec21 Dec22
Additional Paid-In Capital
- 35.50 36.38

iLearningEngines Semi-Annual Data
Dec20 Dec21 Jun22 Dec22 Jun23
Additional Paid-In Capital - 35.50 - 36.38 36.38

iLearningEngines Additional Paid-In Capital Calculation

Capital that a company raises in a financing round in excess of the capital's par value. The account represents the excess paid by an investor over the par-value price of a stock issue. Additional paid-in-capital can arise from issuing either preferred or common stock.

Additional Paid-In Capital is calculated as

Additional Paid-In Capital=(Issue Price-Par Value)* Shares Outstanding (Diluted Average)

iLearningEngines Additional Paid-In Capital 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.