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.
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- Oil Gas and Chemicals
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | VAR/SI | Insight | Insight Source |
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Woodside Energy | Oil, Gas and Chemicals | 4718 | $8.6B | Australia | Amazon Web Services (AWS) | Amazon SageMaker | ML and Data Science Platforms | 2019 | n/a | ||
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Woodside Energy | Oil, Gas and Chemicals | 4718 | $8.6B | Australia | Amazon Web Services (AWS) | Amazon RoboMaker | Robotic Process Automation | 2019 | n/a | In 2019 Woodside Energy implemented Amazon RoboMaker as part of a program to apply reinforcement learning for robotic manipulation, engaging Max Kelsen to develop and open source RoboMaker and RLEstimator components. The work is categorized under Robotic Process Automation and focused on building repeatable robotics ML pipelines to train, tune, and deploy reinforcement learning agents for manipulation tasks that are repetitive or dangerous. The implementation integrated Amazon RoboMaker with Amazon SageMaker using Kubeflow operators, delivering Amazon SageMaker RL Components for Kubernetes that run as steps in Kubeflow pipelines. Functional modules included SageMaker training jobs, AWS RoboMaker simulation jobs, Kubeflow pipeline definitions via the Kubeflow Pipelines SDK, and orchestration primitives to parallelize and sequence RL training, simulation, and deployment steps. Technical integration points were explicit, the solution used open source libraries such as Ray to coordinate distributed RL training, Gazebo for robot simulation, and ROS to preserve robot runtime structure from simulation to production. Trained RL agent models were stored in Amazon Simple Storage Service buckets, and Amazon SageMaker inference nodes were instantiated to support production deployment, with the final model downloaded to robots using the same ROS structure used in simulation. Governance and workflow changes centered on shifting stitching work out of individual data scientist and roboticist tasks into reusable Kubeflow components, enabling pipeline-driven experiment iteration and automated invocation of SageMaker and RoboMaker jobs. Max Kelsen designed the components to be loaded into Kubeflow pipelines so teams can describe and version their robotics ML workflows without manually wiring underlying cloud calls. Outcomes from the engagement included AWS launching Amazon SageMaker Reinforcement Learning Kubeflow Components supporting AWS RoboMaker, and an operational framework that shortens the effort to experiment and manage end-to-end robotics ML workflows from perception to controls. The framework allowed Woodside Energy roboticists and data scientists to concentrate on algorithms and implementation rather than infrastructure orchestration. | |
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Oil, Gas and Chemicals | 4718 | $8.6B | Australia | Amazon Web Services (AWS) | Amazon SAM | Apps Development | 2020 | n/a |
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Oil, Gas and Chemicals | 4718 | $8.6B | Australia | Amazon Web Services (AWS) | Amazon CloudFormation | Infrastructure as Code (IaC) | 2020 | n/a |
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Oil, Gas and Chemicals | 4718 | $8.6B | Australia | Jenkins | Jenkins | API Management | 2016 | n/a |
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Oil, Gas and Chemicals | 4718 | $8.6B | Australia | Wilson Security | Wilson Security Services | Physical Security Outsourcing | 2018 | n/a |
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Oil, Gas and Chemicals | 4718 | $8.6B | Australia | ION Investment Group | Reval Cloud Platform | Treasury Management | 2012 | n/a |
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Oil, Gas and Chemicals | 4718 | $8.6B | Australia | Bubble Group | Bubble Platform | Apps Development | 2023 | n/a |
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Oil, Gas and Chemicals | 4718 | $8.6B | Australia | SAP | SAP S/4 HANA | ERP Financial | 2022 | Deloitte Central Europe |
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Oil, Gas and Chemicals | 4718 | $8.6B | Australia | SAP | SAP Ariba | Procurement | 2022 | n/a |
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