Interfacing Integrated Management System (IMS)
Interfacing’s Integrated Management System (IMS ) is an AI-supported platform that brings BPM, QMS, Document Control, and GRC together in one environment. Teams use IMS to design and manage processes, govern documentation, oversee risks, and demonstrate compliance with complete visibility and reliable audit evidence.
Built for sectors that depend on strict oversight, such as aerospace, life sciences, public sector, and financial services, IMS offers real-time monitoring, automated workflows, and AI-driven analytics that strengthen quality and lower operational exposure. The system is ISO 27001 certified and validated for 21 CFR Part 11, ensuring secure and compliant use in regulated operations. IMS also provides low-code automation, process mining, audit tools, training management, CAPA workflows, and dashboards that help organizations improve performance and maintain regulatory control. AI enhances governance, improves precision, and supports continuous compliance.
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RaimaDB
RaimaDB, an embedded time series database that can be used for Edge and IoT devices, can run in-memory. It is a lightweight, secure, and extremely powerful RDBMS. It has been field tested by more than 20 000 developers around the world and has been deployed in excess of 25 000 000 times.
RaimaDB is a high-performance, cross-platform embedded database optimized for mission-critical applications in industries such as IoT and edge computing. Its lightweight design makes it ideal for resource-constrained environments, supporting both in-memory and persistent storage options. RaimaDB offers flexible data modeling, including traditional relational models and direct relationships through network model sets. With ACID-compliant transactions and advanced indexing methods like B+Tree, Hash Table, R-Tree, and AVL-Tree, it ensures data reliability and efficiency. Built for real-time processing, it incorporates multi-version concurrency control (MVCC) and snapshot isolation, making it a robust solution for applications demanding speed and reliability.
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AWS IoT TwinMaker
Leverage your current IoT, video, and enterprise application data in its existing location, eliminating the need for data reingestion or relocation. Benefit from an automatically created knowledge graph that interconnects your data sources with virtual representations of physical systems, enabling precise modeling of real-world scenarios. Experience an immersive 3D visualization of your operations and systems, enhancing efficiency, boosting production, and elevating performance levels. AWS IoT TwinMaker simplifies the process for developers to create digital twins of tangible systems, including buildings, factories, industrial machinery, and production lines. With AWS IoT TwinMaker, you gain access to essential tools for developing digital twins that optimize building management, augment production capacity, and enhance equipment functionality. Additionally, by utilizing data from various sources, you can construct virtual models of any physical setting while integrating existing 3D models with real-time data for comprehensive insights. This capability allows for a more informed decision-making process, ultimately driving better outcomes in operational strategies.
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DC-E DigitalClone for Engineering
DigitalClone®, for Engineering is the only software that integrates multiple scales of analysis into a single package. It is the world's best gearbox reliability prediction tool. DC-E, in addition to the modeling and analysis capabilities at the level of the gearbox and the gear/bearing, is the only software that models fatigue life using detailed, physics-based models (US Patent 10474772B2).
DC-E allows the construction of a digital twin of a gearbox. This includes all stages of the asset's lifecycle, from design and manufacturing optimization to supplier selection to failure root cause analysis to condition based maintenance and prognostics. This computational environment reduces the time and cost of bringing new designs to market and maintaining them over time.
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