Data Meaning

In 2013, Microsoft Research alumni Yinglian Xie and Fang Yu recognized a critical gap in fraud detection: traditional rules-based systems were failing to catch sophisticated, coordinated attacks that disguised themselves as legitimate user behavior. They founded DataVisor with a mission to restore online trust by pioneering unsupervised machine learning technology that could detect fraud patterns without relying on predefined rules or historical labels. Today, DataVisor has evolved into the world's leading AI-powered fraud and risk platform, protecting over 2 billion accounts globally for Fortune 500 companies across financial services, fintech, e-commerce, and digital payments. The company's comprehensive SaaS platform combines patented unsupervised machine learning with advanced device intelligence and a powerful decision engine to provide end-to-end protection across the entire customer lifecycle - from onboarding to transaction monitoring and anti-money laundering compliance.

We're a team of engineers and researchers who started Databricks in 2013 with a simple but ambitious goal: make data and AI accessible to everyone, not just the technical experts. Our founders created Apache Spark at UC Berkeley, and we've spent the last decade building on that foundation to create a unified platform that brings together data engineering, data science, and machine learning. Today, more than 15,000 organizations worldwide - including over 60% of the Fortune 500 - use our Data Intelligence Platform to solve their toughest data challenges. We believe in open source and have contributed projects like Delta Lake, MLflow, and Unity Catalog to the community. Our lakehouse architecture combines the best of data warehouses and data lakes, giving teams a single source of truth for all their data and analytics work. Whether you're building ETL pipelines, training machine learning models, or powering generative AI applications, we provide the tools and infrastructure to make it happen at scale. We're headquartered in San Francisco but operate globally, working with partners and customers across industries to help them put their data to work.

We're building the monitoring and security platform for cloud applications, bringing together data from servers, containers, databases, and third-party services into one unified view. Founded in 2010 in New York City, we started because the cloud was still relatively immature and engineers needed better visibility into their infrastructure. Today, our platform helps teams see inside any stack, any app, at any scale, anywhere - so they can troubleshoot faster and build more reliable systems. Our SaaS-based platform combines infrastructure monitoring, application performance monitoring, log management, security monitoring, digital experience tracking, and AI-powered insights. We went public in 2019 and have grown to over 8,000 employees worldwide, but we've maintained our focus on solving the real problems engineers face every day. Whether it's tracking down a slow database query, debugging a production incident, or securing cloud infrastructure, we're here to make the complex world of modern software a little more understandable.

We are a trusted global innovator of IT and business services, delivering practical and scalable technology solutions that help clients navigate their digital journey. Part of the NTT Group and headquartered in Tokyo, we serve approximately 75% of the Fortune Global 100, combining deep industry expertise with cutting-edge capabilities in consulting, applications, managed services, and digital transformation. Our team of more than 190,000 professionals operates across over 70 countries, united by a commitment to creating technology for good. At NTT DATA, we believe in respecting every voice, thinking big and being bold, delivering the outcomes we promise, and winning together as one global team. We invest heavily in innovation - backed by $3 billion in annual R&D from NTT Group - and we're on track to become a Global Top 5 IT services provider. From regenerating rainforests with AI to helping organizations harness the power of cloud, cybersecurity, and generative AI, we work every day to shape a better, more sustainable future for our clients, employees, and society.

In an increasingly volatile world where crises unfold in real-time across physical, digital, and cyber domains, organizations face a critical gap: the time between when an event occurs and when they can respond. Dataminr exists to close this gap completely, delivering the earliest actionable intelligence on breaking events, emerging threats, and unexpected risks. The company's AI platform processes more than one million unique public data sources, synthesizing terabytes of data spanning text, images, video, audio, and sensor signals across 150+ languages and 220+ countries and territories. Dataminr's pioneering ReGenAI technology combines Predictive AI and Generative AI to automatically regenerate real-time briefs as events unfold, while its new Intel Agents autonomously generate critical context without prompts. Trusted by more than 100 U.S. government agencies, 20+ international governments, two-thirds of the Fortune 50, and half of the Fortune 100, Dataminr protects people, assets, and operations. From the battlefield to the boardroom, the company enables faster, more informed decisions when seconds matter most, transforming how organizations respond to fast-emerging risks.

We're on a mission to make business better with AI. Since our founding in 2012, DataRobot has been working to help organizations harness the power of artificial intelligence to solve real-world problems. Headquartered in Boston with a global team, we've spent over a decade learning from our customers and evolving our platform to meet the changing needs of enterprises worldwide. We believe AI should be accessible, governable, and impactful - not just a buzzword or an endless pilot project that never makes it to production. Our platform delivers predictive and generative AI capabilities that integrate directly into core business processes. We help teams build, deploy, and govern AI at scale, with the controls and observability needed to minimize risk while maximizing business impact. From agentic AI applications to machine learning models that drive critical decisions, we're focused on practical outcomes. We work across industries - financial services, healthcare, manufacturing, government, and more - because we've seen that the challenges of implementing AI are often similar even when the use cases differ. Our goal is to be the AI partner that helps organizations move from experimentation to production, with confidence.