Epicor Connected Process Control
Epicor Connected Process Control provides a simple-to-use software solution that allows you to configure digital work instructions and enforce process control. It also ensures that operations are error-proof. Connect IoT devices to collect 100% time studies and process data, images and images at the task level. Real-time visibility and quality control on a new level! eFlex can handle any number of product variations or thousands of parts, whether you are a component-based or model-based manufacturer. Work instructions can be linked to Bill of Materials, ensuring that products are built correctly every time, even if changes are made during the process. Work instructions that are part a system that is advanced will automatically react to model and component variations and only display the right work instructions for what's currently being built at station.
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Proton Pass
Proton Pass for Business is a privacy-first password and identity manager that helps organizations secure access at scale without sacrificing usability. Built with end-to-end encryption and a strict zero-knowledge architecture, it ensures that passwords, passkeys, secure notes, and payment details remain accessible only to authorized users within your team. Not even Proton can view your data.
Teams can securely create, store, and share credentials via encrypted vaults, enabling safe and efficient collaboration. Granular admin controls allow IT managers to oversee permissions, enforce strong password policies, monitor access, and manage users throughout the employee lifecycle from onboarding to offboarding. Built-in password generation, autofill, and cross-device syncing streamline everyday workflows while maintaining high security standards.
Proton Pass for Business also includes advanced features such as email alias integration to protect employee identities, dark web monitoring to detect compromised credentials, and detailed activity logs for visibility and compliance. Its open-source foundation promotes transparency and trust, and independent audits reinforce its security model.
Hosted in Switzerland and protected by strong privacy laws, Proton Pass offers organizations a secure alternative to traditional password managers. With seamless browser extensions, an intuitive design, and enterprise-ready controls, it empowers teams to reduce credential-related risks, prevent unauthorized access, and improve productivity, all within a secure, encrypted environment.
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Findora
Establish financial infrastructures that prioritize privacy while maintaining transparency. Findora facilitates the management of various asset types, including dollars, bitcoin, equities, debts, and derivatives. The platform's objective is to tackle the complexities involved in catering to a wide array of assets and financial applications, ensuring confidentiality alongside the transparency typically associated with other blockchains. Utilizing advanced techniques such as zero-knowledge proofs and secure multi-party computation, Findora implements numerous privacy-enhancing features. Its specialized zero-knowledge proofs ensure that while the system can be audited publicly, sensitive data remains protected. Additionally, Findora boasts a high-throughput ledger architecture and minimizes storage needs through the use of cryptographic accumulators. The platform effectively dismantles data silos, facilitating seamless interoperability between main and side ledgers. Furthermore, Findora equips developers with essential tools, thorough documentation, and dedicated support for building their applications. By engaging with the Findora testnet, developers can start creating privacy-focused applications today, paving the way for innovative financial solutions.
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Flower
Flower is a federated learning framework that is open-source and aims to make the creation and implementation of machine learning models across distributed data sources more straightforward. By enabling the training of models on data stored on individual devices or servers without the need to transfer that data, it significantly boosts privacy and minimizes bandwidth consumption. The framework is compatible with an array of popular machine learning libraries such as PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, and XGBoost, and it works seamlessly with various cloud platforms including AWS, GCP, and Azure. Flower offers a high degree of flexibility with its customizable strategies and accommodates both horizontal and vertical federated learning configurations. Its architecture is designed for scalability, capable of managing experiments that involve tens of millions of clients effectively. Additionally, Flower incorporates features geared towards privacy preservation, such as differential privacy and secure aggregation, ensuring that sensitive data remains protected throughout the learning process. This comprehensive approach makes Flower a robust choice for organizations looking to leverage federated learning in their machine learning initiatives.
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