Apps Purchases: 10+ Million Software Purchases
Founded in 2010, APPS RUN THE WORLD is a leading technology intelligence and market-research company devoted to the application space. Leveraging a rigorous data-centric research methodology, we ask the simple B2B sales intelligence question: Who’s buying enterprise applications from whom and why?
Our global team of 50 researchers has been studying the digital transformation initiatives being undertaken by 2 million + companies including technographic segmentation of 10 million ERP, EPM, CRM, HCM, Procurement, SCM, Treasury software purchases, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Apps Run The World Buyer Insight and Technographics Customer Database has over 100 data fields that detail company usage of emerging technologies such as AI, Machine Learning, IoT, Blockchain, Autonomous Database, and different on-prem and cloud apps by function, customer size (employees, revenues), industry, country, implementation status, year deal won, partner involvement, Line of Business Key Stakeholders and key decision-makers contact details, including the systems being used by Fortune 1000 and Global 2000 companies.
Apply Filters For 10+ Million Software Purchases
- Professional Services
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | VAR/SI | Insight | Insight Source |
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Bigfinite | Professional Services | 50 | $7M | United States | Amazon Web Services (AWS) | Amazon SageMaker | ML and Data Science Platforms | 2017 | n/a | In 2017, Bigfinite implemented Amazon SageMaker as part of its bigengine platform to support ML and Data Science Platforms workloads on pharmaceutical-manufacturing data. The deployment was positioned to enable real-time predictions and model hosting to address equipment maintenance, process optimization, anomaly detection, and product quality challenges. The implementation exposed built-in solutions designer capabilities that allow Bigfinite customers to edit and configure packaged solutions or create new data science capabilities. Core functional capabilities include real-time model inference, model training orchestration, and support for proprietary algorithms developed in Python and Scala running on Spark clusters for advanced analytics. Architecturally, Amazon SageMaker was integrated into a multi-service AWS stack. Data ingestion originates from laboratory information management systems and manufacturing equipment connected through AWS IoT, with raw data captured and stored in native formats in a controlled data lake on Amazon Simple Storage Service, Amazon S3. Serverless components such as AWS Lambda and AWS Step Functions coordinate distributed processing, Amazon Athena provides serverless query analysis, and Amazon Elastic MapReduce, running Apache Spark, handles big-data processing workloads that feed models in Amazon SageMaker. Governance and operational scope focus on reproducible pipelines and controlled data management, with the S3 data lake and serverless orchestration providing the foundation for model lifecycle workflows. The solution produces real-time predictions and models that help predict cleaning or maintenance needs, identify imminent equipment failure, optimize processes to reduce cost and energy usage, and detect anomalies to improve final product quality, and customers can extend or configure these capabilities through the platform designer. | |
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Fraud.net | Professional Services | 40 | $5M | United States | Amazon Web Services (AWS) | Amazon SageMaker | ML and Data Science Platforms | 2017 | n/a | ||
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Professional Services | 2000 | $444M | Australia | Amazon Web Services (AWS) | Amazon SageMaker | ML and Data Science Platforms | 2016 | n/a |
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Professional Services | 25000 | $6.8B | Canada | Amazon Web Services (AWS) | Amazon SageMaker | ML and Data Science Platforms | 2016 | n/a |
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Professional Services | 4786 | $1.5B | United States | Amazon Web Services (AWS) | Amazon SageMaker | ML and Data Science Platforms | 2016 | n/a |
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Professional Services | 1000 | $250M | United States | Amazon Web Services (AWS) | Amazon SageMaker | ML and Data Science Platforms | 2016 | n/a |
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Professional Services | 389 | $107M | United Kingdom | Amazon Web Services (AWS) | Amazon SageMaker | ML and Data Science Platforms | 2016 | n/a |
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Professional Services | 750 | $1.6B | United States | Amazon Web Services (AWS) | Amazon SageMaker | ML and Data Science Platforms | 2016 | n/a |
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Professional Services | 5000 | $2.3B | United States | Amazon Web Services (AWS) | Amazon SageMaker | ML and Data Science Platforms | 2016 | n/a |
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Professional Services | 40 | $4M | Germany | Google Cloud Machine Learning Engine | ML and Data Science Platforms | 2016 | n/a |
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