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
- Government
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | VAR/SI | Insight | Insight Source |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
 |
Oak Ridge National Laboratory | Government | 7000 | $2.6B | United States | NVIDIA | NVIDIA CUDA | Apps Development | 2014 | n/a | In 2014 Oak Ridge National Laboratory initiated procurement of NVIDIA GPU-accelerated systems, deploying NVIDIA CUDA in the Apps Development category for the Summit supercomputer in the United States. The program centered on integrating NVIDIA Tesla GPUs with the NVIDIA CUDA programming model to enable large scale scientific high performance computing, artificial intelligence, and simulation workloads. The deployment architecture combined GPU-accelerated compute nodes provisioned for parallel dense compute, CUDA-enabled development and runtime stacks, and an operational environment tuned for HPC and AI workloads. Functional capabilities implemented included CUDA-accelerated application runtimes, developer toolchains for porting and optimizing codes, and support for GPU-native simulation and machine learning workflows. Procurement contracts were announced in 2014 and the Summit system became operational in 2018, hosted at Oak Ridge National Laboratory facilities in the United States. Operational scope encompassed national laboratory research programs in materials science, genomics, and physics, where researchers ran large scale simulations and AI experiments on CUDA-accelerated infrastructure. Governance and operational changes focused on adapting research workflows to GPU architectures, establishing code modernization practices for CUDA, and coordinating compute resource scheduling for GPU-heavy jobs. The NVIDIA CUDA deployment for Summit delivered the stated outcome of major speedups for materials, genomics, and physics research through GPU-accelerated execution. | |
 |
The Port Authority of New York & New Jersey | Government | 7000 | $6.0B | United States | Mark43 | Mark43 RMS | Document Management | 2024 | n/a | In 2024 The Port Authority of New York & New Jersey selected Mark43 RMS, deploying Mark43 RMS as the Document Management component of a cloud native public safety suite that also included Mark43 CAD, OnScene and Mark43 Analytics. The decision was scoped to the Port Authority Police Department and targeted records, dispatch and case workflows across the Authority's airports, bridges, tunnels and transit facilities in the New York/New Jersey region. Mark43 RMS was implemented to centralize incident records and case management, while Mark43 CAD was provisioned for dispatch and OnScene was incorporated for field reporting and incident documentation, with Mark43 Analytics providing consolidated reporting and operational insight. The configuration emphasized a cloud native architecture with secure data segregation and role based access controls consistent with large agency records management best practices. Integrations were structured between Mark43 RMS, CAD, OnScene and Analytics to enable near real time information flow between dispatch, field units and records, supporting cross jurisdictional information sharing across the Authority's sites. The initiative highlighted FedRAMP High security compliance as a governing requirement for deployment, shaping data residency, encryption and access governance controls. Operationally the rollout focused on consolidating records workflows and improving data accessibility for officers and investigators across multiple business functions, including patrol operations, investigations and dispatch centers. The program explicitly aims to improve officer efficiency and interagency information sharing, with security governance and standardized records workflows positioned as core elements of the implementation strategy. | |
 |
|
Government | 7000 | $250M | India | HCL Technologies | HCL Digital Experience | Web Content Management | 2017 | n/a |
|
|
|
|
|
Government | 7000 | $250M | India | Google Hosted Libraries | Content Delivery Network | 2018 | n/a |
|
|
|
|
|
|
Government | 7000 | $250M | India | DigiCert | DigiCert SSL | Secure Sockets Layer (SSL) | 2019 | n/a |
|
|
|
|
|
Government | 7000 | $250M | India | Google Tag Manager | Tag Management | 2019 | n/a |
|
|
|
|
|
|
Government | 7000 | $250M | India | Cisco Systems | Cisco Webex Meetings | Audio Video and Web Conferencing | 2020 | n/a |
|
|
|
|
|
Government | 7000 | $250M | India | AppDynamics | AppDynamics APM | Application Performance Management | 2020 | n/a |
|
|
|
|
|
Government | 7000 | $250M | India | Drupal | Drupal CMS | Web Content Management | 2022 | n/a |
|
|
|
|
|
Government | 7000 | $250M | India | jsDelivr | jsDelivr CDN | Content Delivery Network | 2022 | n/a |
|
|