Turium was created with the vision to enable everybody, regardless of their technical literacy, to build data applications seamlessly without worrying about the underlying system. With this in mind, the founders wanted to design a single platform that provides comprehensive data-delivery capabilities with metadata activation through AI and ML assist.

FABRIQn specialises in systems integration and interoperability solutions, with a focus on knitting disparate databases, IOT systems, apps, and platforms together, so each component works together harmoniously, producing insights in real-time and delivering a capability greater than just the sum of its elements. It is designed to reduce the cost of data integration over time through a rich suite of capabilities and developed to serve as the data integration intelligence for the most complex environments in the world. It consists of hundreds of distinct services that cover a wide range of functionality.

FABRIQn ’s novel attempt at the multi-layered Ontology assimilates data and models into a comprehensive semantic model of the business. FABRIQn application frameworks evolve analytics into operational workflows that enable user action, alerting, and other frontline functions. Low-code and no-code application building, which automates the management of underlying storage, compute, data, and security enforcement; an application development framework with live preview; and APIs, webhooks, and other interfaces that allow for full-spectrum integration within the enterprise. Capabilities include both point-and-click and code based tools that enable table-based analysis, top down visual analysis, geospatial analysis, time series analysis, scenario simulation, and more. Analytics in FABRIQn goes beyond conventional “read-only” paradigms to write data back into Ontology, producing valuable new insights within unified security, lineage, and governance models. It features the best-in-class security model that propagates across the entire platform and remains with data wherever it travels by default. Capabilities include encryption of all data, both in transit and at rest; authentication and identity protection controls; authorisation controls; robust security audit logging; and highly extensible information governance, management, and privacy controls.

Most enterprise teams have varying levels of machine learning expertise, ranging from novices all the way to experts. To accelerate AI innovation through data-driven decision precision, you need a platform that can bring key decision-makers, operational staff, and data scientists together, offering a seamless yet flexible Machine Learning environment. This is where ALGOREUS comes in. It provides purpose-built tools to help you automate and standardise processes across the ML lifecycle. An ML Spawner that lets enterprises: train, test, troubleshoot, deploy, and govern the entire ML lifecycle at scale to boost productivity across all chains of command while maintaining model performance in production with confidence. It accelerates time to value with industry-leading machine learning operations and open-source interoperability. The dependable platform is intended for responsible AI applications, with built-in fairness and explainability. It offers a dedicated solution for training a high quality model with minimal effort through AutoML or training your case-specific models from scratch with CustomML and even managing those produced by third parties. We empower enterprise teams to build to protect against model drift and retain a competitive advantage by providing a solution to continuously test, iterate, and retest models before pushing them to systems at the edge. By pushing only quality transmissions, our software frees tactical bandwidth while providing greater strategic value for the strategic and operational chain of command.

Features of our Offering:

• Ingest and filter everything (big data), Compute Lightning-fast, Born to SCALE, Escape from black-box on all touch points (Responsible Ai),

• Multi-Layered Ontology, Automate entire ML lifecycle, ML Model Registry and Monitor

• Flexible portability (Cloud, Hybrid-cloud, Multi-cloud, Edge processing), Enterprise-grade security, LOW-CODE and NO-CODE (Drag-and-drop interface)

• Model Deployment, Operationalisation and Edge AI, Integration Metadata and Lineage, Collaborative ML and Data Engineering