Iris Identity Protection
Iris provides integration-ready identity and cyber protection solutions that help organizations add powerful customer security capabilities directly into their existing products — without building from scratch. Designed for modern digital platforms, Iris makes it easy to embed identity protection into apps, portals, and customer experiences at scale.
Identity Protection API
Iris’ API suite delivers a multitude of protection solutions—including dark web monitoring & alerts, credit services, risk assessment tools, device protection, and more—into your platform. Teams can fully control the user experience, data flows, and customer journeys while leveraging Iris’ underlying technology and data aggregation.
Micro-Experiences
Prebuilt, customizable UI components that can be embedded directly into your application. These lightweight modules allow teams to quickly deploy identity protection features — such as alerts, dashboards, and monitoring tools — with minimal development effort.
Built for flexibility, Iris supports multiple integration approaches, enrollment methods, and data handling models, so organizations can choose how information flows between users, their systems, and Iris. The platform is designed to scale across large user bases while maintaining strong security and performance standards.
By making identity protection a native part of the user experience, Iris helps organizations increase engagement, strengthen trust, and deliver meaningful, always-on protection to their customers.
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Chainguard
Chainguard Containers provide a trusted set of minimal, zero-CVE container images with a top-tier CVE remediation SLA—addressing critical vulnerabilities within 7 days, and high, medium, and low within 14—enabling teams to build and deploy software more confidently.
As modern development workflows and CI/CD pipelines depend on secure, up-to-date containers for cloud-native applications, Chainguard offers streamlined images built entirely from source in a hardened, secure build environment. Designed for both engineering and security stakeholders, Chainguard Containers reduce the manual overhead of managing vulnerabilities, improve application resilience by shrinking the attack surface, and accelerate go-to-market by simplifying alignment with compliance standards and customer security expectations.
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µVision IDE
The µVision Integrated Development Environment (IDE) brings together various functionalities such as project management, run-time environment, build tools, source code editing, and program debugging into one robust platform. User-friendly and efficient, µVision enhances the speed of embedded software development processes. It also accommodates multiple screens, enabling users to customize their workspace with unique window layouts across the interface. The µVision Debugger offers a comprehensive setting where you can test, validate, and fine-tune your application code effectively. It features an array of traditional debugging tools, including both simple and complex breakpoints, watch windows, and control over execution, ensuring complete access to device peripherals. By leveraging the µVision Project Manager and Run-Time Environment, developers can construct software applications using pre-assembled software components and device support sourced from Software Packs. These software components encompass libraries, source modules, configuration files, templates for source code, and thorough documentation, providing a well-rounded foundation for development. This holistic approach not only streamlines the development process but also significantly reduces the time taken to bring projects to completion.
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Byne
Start developing in the cloud and deploying on your own server using retrieval-augmented generation, agents, and more. We offer a straightforward pricing model with a fixed fee for each request. Requests can be categorized into two main types: document indexation and generation. Document indexation involves incorporating a document into your knowledge base, while generation utilizes that knowledge base to produce LLM-generated content through RAG. You can establish a RAG workflow by implementing pre-existing components and crafting a prototype tailored to your specific needs. Additionally, we provide various supporting features, such as the ability to trace outputs back to their original documents and support for multiple file formats during ingestion. By utilizing Agents, you can empower the LLM to access additional tools. An Agent-based architecture can determine the necessary data and conduct searches accordingly. Our agent implementation simplifies the hosting of execution layers and offers pre-built agents suited for numerous applications, making your development process even more efficient. With these resources at your disposal, you can create a robust system that meets your demands.
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