SciSure is a Scientific Management Platform built to support the full range of laboratory operations for scientific organizations. It combines ELN, LIMS, and Health & Safety functionality, giving teams a single system to document experiments, track sample lineage, manage chemical inventory, and run structured, audit-ready compliance processes.
Instead of relying on disconnected systems, organizations get one governed platform that improves reproducibility, increases visibility into lab operations, and reduces risk as they scale.
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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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SeqOne
SeqOne is an advanced genomic analysis platform powered by artificial intelligence, aimed at enabling molecular laboratories, clinical teams, biologists, and geneticists to convert intricate next-generation sequencing data into quick, accurate, and actionable clinical insights that aid in personalized medicine diagnostics. By streamlining the entire genomic workflow—from handling raw sequencing data to variant interpretation and reporting—this platform automates routine tasks, integrates smoothly with laboratory systems, and employs sophisticated AI models like DiagAI to assess and prioritize disease-related variants, thereby minimizing manual labor and shortening turnaround times. SeqOne is versatile, catering to both germline and somatic analyses across various fields such as oncology, rare inherited diseases, and infectious disease detection, while it combines high-quality annotation databases and standardized interpretation protocols to ensure clinical-grade precision. Furthermore, it features an intuitive user interface that can scale securely through the cloud, making it accessible and efficient for diverse clinical environments. Ultimately, SeqOne represents a significant advancement in genomic analysis technology, fostering enhanced diagnostic capabilities in the realm of personalized medicine.
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Gesund.ai
Gesund stands as the pioneering compliant AI factory dedicated to facilitating the introduction of clinical-grade AI solutions into the market. In order to meet regulatory standards, our platform meticulously audits and validates third-party medical AI solutions, ensuring their safety, effectiveness, and fairness. Gesund seamlessly manages the entire AI/ML lifecycle for all participants by integrating models, data, and expertise within a user-friendly no-code environment. We offer standardized, cohesive, and diverse data tailored to meet your machine learning requirements and regulatory obligations. By evaluating the validation needs of models, Gesund.ai supplies an optimal combination of high-quality data sourced from its extensive network of clinical partners. Model owners can share their clinical studies with Gesund.ai to curate the necessary datasets, subsequently uploading their models onto Gesund.ai's federated validation platform, which can be situated on hospital premises or within a private cloud. Each model undergoes evaluation against a validation dataset that has been specifically curated on the hospital side, ensuring that the results are relevant and reliable, ultimately enhancing the quality of healthcare solutions. Through this comprehensive approach, Gesund not only supports compliance but also accelerates the path to effective AI deployment in clinical settings.
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