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
- Retail
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | VAR/SI | Insight | Insight Source |
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Lovehoney | Retail | 221 | $109M | United Kingdom | Deepchecks | Deepchecks LLM Evaluation | MLOps Platforms | 2025 | n/a | In 2025, Lovehoney Group implemented Deepchecks LLM Evaluation to test and monitor a RAG-enabled customer service chatbot. The UK-based deployment used Deepchecks LLM Evaluation within the MLOps Platforms category to accelerate experiments while validating responses against brand and safety guidelines. Deepchecks LLM Evaluation was configured to run automated evaluation pipelines, combining staged testing of RAG responses with continuous drift detection and policy checks for safety and brand alignment. The implementation focused on experiment velocity and short iteration cycles, enabling rapid adjustments to prompt templates, retrieval behavior, and response ranking during evaluation and production testing. Operational scope concentrated on customer service workflows within Lovehoney’s UK support organization, moving from evaluation to production within weeks and activating continuous monitoring in production to detect model performance drift. Governance was established through policy-driven evaluation gates and ongoing monitoring rules that enforced brand and safety criteria before and after deployment. Outcomes reported by the project included roughly 5× faster iteration time and continuous drift detection in production, with the platform used to maintain response safety and brand alignment during live operation. The deployment positioned Deepchecks LLM Evaluation as the operational MLOps Platforms capability for lifecycle testing and monitoring of Lovehoney’s customer-facing generative AI. | |
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Jack in the Box | Retail | 1079 | $1.7B | United States | Deepgram | Deepgram Text to Speech | Chatbots and Conversational AI | 2025 | n/a | In 2025, Jack in the Box deployed Deepgram Text to Speech as part of a Chatbots and Conversational AI initiative to power real time voice agents for customer service contact center and drive thru automation across the United States. Deepgram Text to Speech is used in combination with Deepgram's Voice Agent API to bind speech to text and text to speech into conversational call flows that handle order taking and automated responses. The implementation centers on speech to text capture, text to speech synthesis, conversational orchestration and session management to support live audio streaming and two way conversational exchanges. Standard Chatbots and Conversational AI capabilities such as intent recognition and dialog management are applied to route interactions, surface prompts, and trigger order capture workflows. Configuration includes voice model tuning and prompt engineering to align synthesized voice output with Jack in the Box brand tone. Integrations connect the Deepgram deployment to contact center telephony platforms and drive thru audio ordering systems, enabling automatic order capture and escalation to human agents when needed. Operational scope covers customer service and drive thru operations across sites in the United States, with the application influencing call handling, order processing, and front line operations. The system design supports session handoff between automated voice agents and live agents to preserve continuity of customer conversations. Governance focuses on runtime monitoring, conversational quality measurement, and iterative voice model adjustment to maintain accuracy and customer experience. The deployment aims to reduce wait times and lower operational costs as stated in project objectives. | |
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Retail | 100 | $15M | United States | Displai Systems | Displai Digital Signage | Digital Signage | 2025 | n/a |
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Retail | 376000 | $134.2B | Germany | DoubleVerify | DV Authentic AdVantage | Marketing Analytics | 2025 | n/a |
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Retail | 22214 | $10.5B | Germany | DoubleVerify | DV Authentic AdVantage | Marketing Analytics | 2025 | n/a |
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Retail | 200 | $25M | United States | Dropbox | Dropbox Dash | Document Management | 2025 | n/a |
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Retail | 80 | $10M | United States | Duo Security | Duo Directory | Identity and Access Management (IAM) | 2025 | n/a |
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Retail | 43435 | $11.9B | Netherlands | Effectory | Effectory Employee Feedback | Employee Engagement | 2025 | n/a |
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Retail | 381000 | $37.2B | United States | Enlyte | Enlyte Genex | Case Management | 2025 | n/a |
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Retail | 11000 | $1.7B | United States | Fluent Commerce | Fluent Big Inventory | Inventory Management | 2025 | n/a |
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