SDMS

TetraScience's Universal SDMS (Scientific Data Management System) is a vendor-agnostic, cloud-based platform purpose-built to transform the way life sciences organizations handle their scientific and laboratory data. Designed for both Scientific IT teams and bench scientists, it replaces legacy SDMS solutions, LIMS-centric approaches, and costly in-house builds with a unified, enterprise-scale platform that centralizes, contextualizes, and makes scientific data freely accessible for collaboration, analytics, and AI-driven innovation.

Unlike traditional SDMS tools that create data graveyards or lock organizations into a single vendor's ecosystem, TetraScience's Universal SDMS serves as a central repository for all internal and external scientific data—connecting instruments, software, ELNs, LIMS, and legacy systems at unprecedented scale while enabling long-term data reuse and regulatory compliance.

Core Platform Capabilities

• Centralize petabytes of scientific data from any source in an enterprise-scale, purpose-built data platform accessible to teams anywhere, at any time
• Connect instruments, software, and legacy SDMS using the world's largest and fastest-growing library of purpose-built, industrialized integrations—with more than 1,000 instruments connected and 10 new integrations added per day
• Automatically augment data with scientifically relevant metadata from any ELN or LIMS to make information findable, searchable, and reusable
• Archive and restore raw and processed (primary and secondary) data with complete audit trails and visual traceability
• Group raw data with related analysis results from both manual and automated uploads for richer scientific context
• Support a data lakehouse architecture that enables analytics and AI use cases at scale

Data Lineage and Compliance

• Maintain full data provenance from capture to archival with a complete chain of custody for regulatory compliance
• Store, archive, and retrieve data with full audit trails and visual traceability to and from ELN and LIMS platforms
• Track all data alterations with human-in-the-loop audit trails and sign-off events as required
• Unique data lineage tools reduce the likelihood of repeated experiments—organizations using data lineage are 7x less likely to repeat experiments
• Reduce the 40% of scientist time typically spent aggregating data for reuse

Benefits for Scientific IT Teams

• Eliminate bespoke point-to-point integrations with hundreds of disparate data sources
• Leverage the largest library of integrations to replatform all scientific and lab data to the cloud
• Build and deploy custom parsers, pipelines, and integrations using self-service tools while maintaining full control to scale and evolve workflows
• Create and manage lab data automation pipelines with self-service schemas to curate datasets for analytics and AI
• Build or bring your own applications with no IT or network provisioning required
• Develop upon a growing library of integrations, schemas, pipelines, and recipes within a collaborative ecosystem

Benefits for Scientists

• Retrieve current and historical data and results from your own and other teams' repositories with ease
• Get a comprehensive overview of all data and any activities related to files
• Easily compile data for reports and regulatory filings
• Track data with unique lineage tools to avoid repeating experiments due to missing historical data
• Ensure regulatory compliance with minimal effort, freeing more time to focus on science

Universal SDMS vs. Traditional and Legacy Approaches

• Traditional SDMS tools are typically offered by instrument vendors or LIMS providers, resulting in vendor lock-in; TetraScience is fundamentally vendor-agnostic
• Legacy SDMS solutions are mainly designed for data storage and archival, creating data graveyards that hinder automation, analytics, and AI; TetraScience is purpose-built to enable lab data automation and data reuse
• Legacy approaches are focused on endpoints and capture limited data, complicating cross-department and cross-partner comparisons; TetraScience includes the largest library of integrations to make all scientific data accessible to any LIMS or ELN
• Middleware solutions handle data movement only with endpoint-centric integrations, while TetraScience provides full data engineering capabilities including schema, taxonomy, and ontology management
• New Review by Exception capabilities further boost quality operations through smarter, exception-driven review workflows

TetraScience's Universal SDMS has ingested over 3 petabytes of data in a single year and supports managing external partner data from CROs, CDMOs, and CMOs. The platform integrates with leading analytics and AI environments such as Snowflake and Databricks, and is trusted by leading life sciences organizations including Andelyn Biosciences and Takeda to serve as the core platform for scientific data and a strategic accelerator for R&D.