Cody
Cody, Sourcegraph’s AI code assistant goes beyond individual dev productivity, helping enterprises achieve consistency and quality at scale with AI.
Unlike traditional coding assistants, Cody understands the entire codebase, enabling deeper contextual awareness for smarter autocompletions, refactoring, and AI-driven code suggestions. It integrates with IDEs like VS Code, Visual Studio, Eclipse, and JetBrains, providing inline editing and chat without disrupting workflows. Cody also connects with tools like Notion, Linear, and Prometheus to enhance development context. Powered by advanced LLMs like Claude Sonnet 4 and GPT-4o, it optimizes speed and performance based on enterprise needs, and is always adding the latest AI models. Developers report significant efficiency gains, with some saving up to six hours per week and doubling their coding speed.
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UserWay
UserWay is a leader in digital accessibility compliance, committed to empowering the fundamental human right for inclusive digital experiences and usability. Trusted by over 1 million websites across the globe, UserWay’s AI-powered technologies break down barriers hindering digital inclusion, ensuring that every digital interaction is seamless and user-friendly.
UserWay’s team of web accessibility experts combine a deep legal and technical prowess, ensuring compliance with multiple global laws and standards, including WCAG 2.2, ADA, EN 301-549, and Section 508.
In addition to the cutting-edge Accessibility Widget, UserWay's suite of offerings include the Accessibility Scanner that automates violation detection and remediation, and manual Accessibility Audits. Their Accessibility Plugin provides native integration for seamless accessibility enhancement.
Discover why millions of users rely on UserWay’s accessibility solutions for inclusion and compliance.
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CUDA
CUDA® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs.
In GPU-accelerated applications, the sequential part of the workload runs on the CPU – which is optimized for single-threaded performance – while the compute intensive portion of the application runs on thousands of GPU cores in parallel. When using CUDA, developers program in popular languages such as C, C++, Fortran, Python and MATLAB and express parallelism through extensions in the form of a few basic keywords.
The CUDA Toolkit from NVIDIA provides everything you need to develop GPU-accelerated applications. The CUDA Toolkit includes GPU-accelerated libraries, a compiler, development tools and the CUDA runtime.
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NVIDIA Confidential Computing
NVIDIA Confidential Computing secures data in use, protecting AI models and workloads as they execute, by leveraging hardware-based trusted execution environments built into NVIDIA Hopper and Blackwell architectures and supported platforms. It enables enterprises to deploy AI training and inference, whether on-premises, in the cloud, or at the edge, with no changes to model code, while ensuring the confidentiality and integrity of both data and models. Key features include zero-trust isolation of workloads from the host OS or hypervisor, device attestation to verify that only legitimate NVIDIA hardware is running the code, and full compatibility with shared or remote infrastructure for ISVs, enterprises, and multi-tenant environments. By safeguarding proprietary AI models, inputs, weights, and inference activities, NVIDIA Confidential Computing enables high-performance AI without compromising security or performance.
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