Free from traditional Scientific Data Management limitations
Traditional data management are often called “data graveyards”, terminal deadends for their inability to support data automation or Scientific AI.Tetra Scientific Data and AI Cloud’s data replatforming layer includes all key functionalities of a traditional SDMS, solving your immediate need for data connectivity and provides the foundation to Scientific AI.
Your immediate need builds the perfect foundation
The Tetra Scientific Data and AI Cloud is new and it is different. It provides all the core functionalities you need from traditional SDMS —and more. You can store, manage, and access your scientific data without limitations. Made for today and for the future, it allows data-centric organizations to share data and collaborate with it. It transforms your data into the atomic building blocks for Scientific AI: AI-native Tetra Data.
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Tetra Scientific Data and AI Cloud, key differentiators
Open and vendor-agnostic
Traditional SDMS is provided by either instrument manufacturers or informatics applications (LIMS) providers, as part of the “walled garden” approach. Our next-gen SDMS ensures true data liquidity provided by TetraScience’s open and vendor agnostic business model.
Purpose-built for scientific data
Get purpose-engineered, compliant data for science. Draw from our science and data expertise. Harmonize your data for scientific applications. Standardize your metadata with science-relevant taxonomies and ontologies. Connect to the world of advanced analytics and Scientific AI.
Collaborative
Innovation depends on collaboration. Collaboration requires liquid, shareable data. Let your data flow seamlessly among scientific teams, partners, CROs, CDMOs, and your larger scientific ecosystem.
AI-native data
Traditional SDMS is provided by either instrument manufacturers or informatics applications (LIMS) providers, as part of the “walled garden” approach. Our next-gen SDMS ensures true data liquidity provided by TetraScience’s open and vendor agnostic business model.
Fundamental
Collect all your valuable scientific data. Connect all your data generators and data consumers through industrialized integrations. Access your data anywhere, anytime. Purpose-engineer your data for reuse with scientific applications and future-proof your scientific data for collaboration and AI.
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