List of FogHorn Lightning EdgeML Customers

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Logo Customer Industry Empl. Revenue Country Vendor Old Product New Product Category When SI
DAIHEN Corporation Manufacturing 3783 $1.2B Japan Johnson Controls Legacy FogHorn Lightning EdgeML ML and Data Science Platforms 2018 n/a
Schindler Elevator Corporation (U.S.) Manufacturing 20000 $10.5B United States Johnson Controls Legacy FogHorn Lightning EdgeML ML and Data Science Platforms 2017 n/a
VIA ELECTRONICS CO., LTD. Manufacturing 1000 $184M Taiwan Johnson Controls Legacy FogHorn Lightning EdgeML ML and Data Science Platforms 2018 n/a
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Buyer Intent: Companies Evaluating FogHorn Lightning EdgeML

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FAQ - APPS RUN THE WORLD FogHorn Lightning EdgeML Coverage

FogHorn Lightning EdgeML is a ML and Data Science Platforms solution from Johnson Controls.

Companies worldwide use FogHorn Lightning EdgeML, from small firms to large enterprises across 21+ industries.

Organizations such as Schindler Elevator Corporation (U.S.), DAIHEN Corporation and VIA ELECTRONICS CO., LTD. are recorded users of FogHorn Lightning EdgeML for ML and Data Science Platforms.

Companies using FogHorn Lightning EdgeML are most concentrated in Manufacturing, with adoption spanning over 21 industries.

Companies using FogHorn Lightning EdgeML are most concentrated in United States, Japan and Taiwan, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of FogHorn Lightning EdgeML across Americas, EMEA, and APAC.

Companies using FogHorn Lightning EdgeML range from small businesses with 0-100 employees - 0%, to mid-sized firms with 101-1,000 employees - 33.33%, large organizations with 1,001-10,000 employees - 33.33%, and global enterprises with 10,000+ employees - 33.33%.

Customers of FogHorn Lightning EdgeML include firms across all revenue levels — from $0-100M, to $101M-$1B, $1B-$10B, and $10B+ global corporations.

Contact APPS RUN THE WORLD to access the full verified FogHorn Lightning EdgeML customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of ML and Data Science Platforms.