
Virtuoso QA is an enterprise agentic test automation platform establishing the standard of proof for software releases. As AI accelerates development, testing must keep pace without compromising confidence. Virtuoso QA delivers this through a governed testing loop for any browser-based application: AI proposes tests, a deterministic engine executes them, a person approves what matters, and every test run leaves evidence. At its core is Touchstone, the agentic layer where specialised agents handle the operational work of testing. The Analyst converts documentation into source-cited test requirements and identifies coverage gaps, the Architect designs the test journeys that validate each requirement, and Autopilot builds those journeys with human approval at key stages. Agents learn your application through the Knowledge Base and follow your team’s testing standards through Agent Directives. As applications change, test fixes are proposed as reviewable diffs, so no test updates without human oversight.
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Denodo is an enterprise data management platform designed to deliver live, unified, governed, and business-ready data for AI agents, analytics, applications, and self-service users. It uses logical data management to connect information across hybrid, multi-cloud, on-premises, SaaS, lakehouse, and third-party environments without moving or duplicating data. The platform helps organizations break down data silos by creating a single trusted access layer over distributed systems. Denodo supports trustworthy AI by giving agents real-time situational awareness, relevant enterprise context, consistent semantics, and compliance guardrails. Its zero-copy approach helps organizations reduce data replication, simplify integration, and avoid delays caused by traditional pipeline-heavy architectures. The platform also provides a personalized data marketplace where users can search, discover, prepare, and use governed data with less IT involvement. Denodo’s governance capabilities enforce consistent policies across cloud and on-premises environments while supporting fine-grained oversight, lineage, and compliance controls. Its real-time query optimization allows teams to make decisions using current data while keeping infrastructure costs under control. Business-contextual semantics help tailor data delivery for different roles, use cases, applications, and AI models. Denodo can support use cases such as AI agents and apps, lakehouse optimization, real-time operations, data products, and enterprise self-service analytics. With faster insight delivery, stronger governance, and trusted data access, Denodo helps organizations create a reliable foundation for agentic AI and modern data-driven operations.
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PathWave RFIC Design
Enhance your methodology for RF simulation by emphasizing the thorough design, scrutiny, and validation of radio frequency integrated circuits (RFICs). Ensure confidence in your projects by leveraging steady-state and nonlinear solvers during both the design and verification stages. Utilizing wireless standard libraries significantly accelerates the process of validating complex RFICs. It is vital to verify IC specifications through RF simulation before finalizing an RFIC, as these simulations account for various elements, including layout parasitics, complex modulated signals, and digital control circuitry. With PathWave RFIC Design, you can conduct simulations across both frequency and time domains, allowing for effortless transitions between your designs and Cadence Virtuoso. Achieve precise modeling of components on silicon chips, and refine your designs by employing optimization techniques such as sweeps and load-pull analysis. The integration of RF designs into the Cadence Virtuoso ecosystem is made more efficient, while the application of Monte Carlo and yield analysis can significantly enhance overall performance. Furthermore, debugging is simplified through safe operating area alerts, enabling the quick adoption of state-of-the-art foundry technologies to maintain a competitive edge in innovation. This comprehensive strategy for RFIC design not only boosts efficiency but also significantly enhances the overall quality and dependability of the resultant products, making it a crucial element in modern electronic design. By adopting this approach, engineers can achieve greater precision and reliability in their RFIC projects, ultimately leading to more successful outcomes in various applications.
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RelationalAI
RelationalAI stands at the forefront of database technology, specifically designed to optimize advanced data applications utilizing relational knowledge graphs. By emphasizing a data-centric approach to application development, it seamlessly integrates data with logic into modular structures. These advanced applications are adept at understanding and leveraging every relationship within a given model. Utilizing a knowledge graph framework, the system articulates knowledge through executable models that can be easily expanded with declarative programs, which are both accessible and user-friendly. The versatile declarative language offered by RelationalAI allows developers to significantly reduce the amount of code needed, achieving reductions between 10 to 100 times, which in turn accelerates application development and improves quality by enabling non-technical users to participate in the creation process while simultaneously automating intricate programming tasks. By harnessing a flexible graph data model, users can establish a strong data-centric infrastructure. Moreover, the integration of various models facilitates the discovery of new relationships, effectively breaking down barriers that separate different applications. This pioneering methodology not only enhances the efficiency of development but also encourages collaboration across multiple domains, ultimately creating a more interconnected ecosystem for innovation. In this way, RelationalAI is redefining the standards for how data applications are built and utilized.
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