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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- Communications
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | VAR/SI | Insight | Insight Source |
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Entel | Communications | 12132 | $2.9B | Chile | HEAVY.AI (formerly OmniSci) | HeavyML | ML and Data Science Platforms | 2023 | n/a | In 2023 Entel deployed HeavyML from HEAVY.AI as part of its ML and Data Science Platforms footprint to accelerate telecom network analytics. The deployment emphasizes interactive mapping and analysis of massive mobile and network datasets to detect performance issues and improve customer experience in Chile. HeavyML's in database predictive modeling capability is used alongside HEAVY.AI interactive analytics to support geospatial visualization and high throughput time series analysis of network telemetry. The implementation concentrates on keeping compute close to data for exploratory analytics and model inference, aligning with ML and Data Science Platforms patterns for large scale telemetry processing. Operational coverage centers on Entel network operations and customer experience teams in Chile, who use the platform to interrogate large mobile and network datasets for performance triage and operational troubleshooting. Integrations are focused on ingesting and querying massive mobile and network data sources, supporting iterative analytics workflows and operational dashboards. Given HEAVY.AI's 2023 HeavyML release of in database predictive modeling, it is reasonable to infer Entel could apply HeavyML for network anomaly detection and capacity forecasting, though use of those specific predictive workflows is inferred rather than explicitly named in Entel's published case study. | |
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Entel | Communications | 12132 | $2.9B | Chile | K2view | K2view | Master Data Management | 2018 | n/a | In 2018 Entel implemented the K2View Data Product Platform, branded as K2view, to build a Multichannel Data Store. The K2view deployment is classified as Master Data Management and was designed to decouple digital channels from backend systems to improve CRM and digital channel performance. Configuration centered on a Multichannel Data Store that fronted an API layer to serve read requests and accelerate transaction processing. The K2view implementation was configured to isolate read traffic and protect core billing and operational systems from massive read loads. Functional capabilities implemented focused on API performance optimization and subsecond response orchestration for CRM and digital channels. Integrations explicitly tied the K2view platform to Entel's CRM and backend operational systems, providing a decoupled data fabric for digital storefronts and customer service channels. The operational rollout covered service delivery across Chile, with expansion to Peru noted as part of the program. The deployment centralized multichannel reads through the data product layer to handle regional channel workloads. The project went live in 2018 to accelerate transaction processing, shield core systems from excessive read traffic, and improve service delivery. Reported outcomes included a 70% improvement in API performance and approximately 200 millisecond average response times for served transactions. Operational risk reduction was achieved by decoupling read traffic, cost or ROI figures were not provided. | |
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Communications | 350 | $50M | Chile | Matomo | Matomo Analytics | Marketing Analytics | 2014 | n/a |
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Communications | 350 | $50M | Chile | Microsoft | Microsoft 365 | Collaboration | 2016 | n/a |
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Communications | 350 | $50M | Chile | Microsoft | Microsoft Azure DNS | Domain Name System (DNS) | 2016 | n/a |
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Communications | 350 | $50M | Chile | Google Hosted Libraries | Content Delivery Network | 2017 | n/a |
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Communications | 350 | $50M | Chile | Cisco Systems | Cisco Webex Meetings | Audio Video and Web Conferencing | 2017 | n/a |
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Communications | 350 | $50M | Chile | Intuit | Intuit Mailchimp | Marketing Automation | 2018 | n/a |
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Communications | 350 | $50M | Chile | Lumen Technologies | Lumen CDN | Content Delivery Network | 2018 | n/a |
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Communications | 350 | $50M | Chile | GlobalSign | GlobalSign SSL RSA | Secure Sockets Layer (SSL) | 2018 | n/a |
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