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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PandoLogic | Professional Services | 80 | $8M | United States | BigML | BigML | ML and Data Science Platforms | 2015 | n/a | In 2015 PandoLogic implemented BigML as its ML and Data Science Platforms solution to bring repeatable predictive modeling into production. The deployment targeted the companys data science and engineering teams at an organization size of approximately 80 employees, with an emphasis on end to end machine learning workflows delivered through a managed BigML service and web console. The implementation centered on standard ML and Data Science Platforms capabilities, including data preprocessing and feature engineering, model training and evaluation, model management and versioning, and programmatic prediction via REST API and batch scoring. BigML was configured to host models and experiments, to automate training pipelines, and to provide experiment tracking and visualization for analysts and developers. Operational integration emphasized API based ingestion from internal data pipelines and batch export for downstream production systems, while governance focused on centralized model cataloging, access controls, and version control to standardize workflows. Rollout proceeded as a staged adoption with core analytic users first and broader engineering consumption following, aligning BigML platform usage with PandoLogics existing software delivery cadence. | |
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Faraday | Professional Services | 30 | $3M | United States | BigML | BigML | ML and Data Science Platforms | 2016 | n/a | In 2016, Faraday implemented BigML to establish a formal machine learning capability within the company. Faraday is a United States based professional services firm with 30 employees, and the deployment positioned BigML as the ML and Data Science Platforms component for its analytics and client delivery functions. The implementation focused on core ML and Data Science Platforms capabilities including data ingestion and preparation, model training and evaluation, automated model selection workflows, and API-based scoring for production use. BigML was configured to support iterative supervised modeling, model export and persistent model artifacts, and scheduled workflows to operationalize recurring training and scoring tasks. Operationally the deployment followed a centralized analytics architecture with BigML providing SaaS style model orchestration and API endpoints for prediction services, enabling integration points into Faraday professional services workflows and client engagements. Governance centered on model versioning, experiment tracking, and role based access for analysts and developers, with rollout scope covering analytics, client delivery, and product-facing prediction pipelines. | |
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Professional Services | 28000 | $4.7B | Germany | BigML | BigML | ML and Data Science Platforms | 2016 | n/a |
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Professional Services | 3210 | $850M | Indonesia | Sift Science | Sift Science Digital Trust Platform | ML and Data Science Platforms | 2016 | n/a |
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Professional Services | 200 | $200M | United States | Sift Science | Sift Science Digital Trust Platform | ML and Data Science Platforms | 2016 | n/a |
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Professional Services | 100 | $20M | Canada | Sift Science | Sift Science Digital Trust Platform | ML and Data Science Platforms | 2016 | n/a |
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Professional Services | 750 | $195M | Germany | Sift Science | Sift Science Digital Trust Platform | ML and Data Science Platforms | 2021 | n/a |
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Professional Services | 33 | $7M | United States | Sift Science | Sift Science Digital Trust Platform | ML and Data Science Platforms | 2020 | n/a |
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Professional Services | 100 | $12M | United States | Sift Science | Sift Science Digital Trust Platform | ML and Data Science Platforms | 2017 | n/a |
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Professional Services | 90 | $35M | United States | Sift Science | Sift Science Digital Trust Platform | ML and Data Science Platforms | 2016 | n/a |
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