Teradata VantageCloud
Teradata VantageCloud: Open, Scalable Cloud Analytics for AI
VantageCloud is Teradata’s cloud-native analytics and data platform designed for performance and flexibility. It unifies data from multiple sources, supports complex analytics at scale, and makes it easier to deploy AI and machine learning models in production. With built-in support for multi-cloud and hybrid deployments, VantageCloud lets organizations manage data across AWS, Azure, Google Cloud, and on-prem environments without vendor lock-in. Its open architecture integrates with modern data tools and standard formats, giving developers and data teams freedom to innovate while keeping costs predictable.
Learn more
Amazon Web Services (AWS)
AWS is the leading provider of cloud computing, delivering over 200 fully featured services to organizations worldwide. Its offerings cover everything from infrastructure—such as compute, storage, and networking—to advanced technologies like artificial intelligence, machine learning, and agentic AI. Businesses use AWS to modernize legacy systems, run high-performance workloads, and build scalable, secure applications. Core services like Amazon EC2, Amazon S3, and Amazon DynamoDB provide foundational capabilities, while advanced solutions like SageMaker and AWS Transform enable AI-driven transformation. The platform is supported by a global infrastructure that includes 38 regions, 120 availability zones, and 400+ edge locations, ensuring low latency and high reliability. AWS integrates with leading enterprise tools, developer SDKs, and partner ecosystems, giving teams the flexibility to adopt cloud at their own pace. Its training and certification programs help individuals and companies grow cloud expertise with industry-recognized credentials. With its unmatched breadth, depth, and proven track record, AWS empowers organizations to innovate and compete in the digital-first economy.
Learn more
GrazeAI
Graze.ai is redefining how organizations discover and enrich critical business data. Built for precision, it automates 1,200+ intelligent steps to clean, interpret, and verify fragmented or missing information—turning messy user inputs into reliable datasets. Its unique machine learning framework, which combines transfer learning, few-shot learning (FSL), and large language model reasoning, enables Graze.ai to understand context like a human researcher while operating at global scale. The platform crawls tens of millions of public sources every week, cross-referencing company names, founders, events, and domains with exceptional accuracy. It filters out human errors, typographical noise, and irrelevant data, ensuring every output is backed by verifiable digital evidence. Top-performing sales and marketing teams use Graze.ai to hyper-target opportunities, reduce wasted spend, and double their conversion efficiency. Customers like Hyre, Breezeful, and Dundas Life credit Graze.ai with driving revenue growth through data that other tools simply miss. With unmatched depth and speed, Graze.ai empowers teams to act on data that’s both complete and correct.
Learn more
Vectice
Empowering all AI and machine learning initiatives within enterprises to yield reliable and beneficial outcomes is crucial. Data scientists require a platform that guarantees reproducibility for their experiments, ensures discoverability of every asset, and streamlines the transfer of knowledge. Meanwhile, managers need a specialized data science solution to safeguard knowledge, automate reporting tasks, and simplify review processes. Vectice aims to transform the operational dynamics of data science teams and enhance their collaboration. The ultimate objective is to foster a consistent and advantageous impact of AI and ML across various organizations. Vectice is introducing the first automated knowledge solution that is not only cognizant of data science but also actionable and seamlessly integrates with the tools utilized by data scientists. The platform automatically captures all assets generated by AI and ML teams, including datasets, code, notebooks, models, and runs, while also creating comprehensive documentation that spans from business requirements to production deployments, ensuring that every aspect of the workflow is covered efficiently. This innovative approach allows organizations to maximize their data science potential and drive meaningful results.
Learn more