TetraScience has launched Tetra Workflows, a transformative platform designed to automate scientific data workflows at scale. Built on the next-generation Scientific Data Management System (SDMS), this solution eliminates manual, error-prone processes, enabling laboratories to accelerate discoveries and improve efficiency in life sciences research.
Tetra Workflows automates scientific data management, reducing manual tasks.
AI-powered tools enable 40% faster creation of custom data integrations.
Visual Pipeline Builder offers no-code solutions for rapid workflow development.
Tetra Data Capture App digitizes data from simple instruments like pH meters.
Pre-configured recipes support integrations with Benchling, Veeva, and more.
Early adopters report 90% reduced implementation time and 75% fewer errors.
Tetra Workflows addresses the complexity of modern laboratory data management, where scientists often spend up to 40% of their time on manual data tasks. By automating the journey from data collection to analysis, the platform ensures data quality, traceability, and efficiency. It integrates seamlessly with electronic lab notebooks (ELNs), laboratory information management systems (LIMSs), and laboratory execution systems (LESs), freeing scientists to focus on research. "Scientists should be focused on science, not wrestling with data management," said Simon Meffan-Main, General Manager at TetraScience.
The Workflow Creation Assistant leverages AI to simplify the creation of custom data integrations. Scientists and IT professionals can map data to LIMS or ELN systems without complex scripting, achieving 40% faster development. The AI proactively identifies data anomalies, ensuring quality and reliability before deployment. This democratizes workflow creation, empowering scientists to build automated processes independently.
The Visual Pipeline Builder provides an intuitive, graphical interface for building automated data pipelines. This no-code and low-code tool enables users to develop multi-step workflows 100% faster, eliminating the need for specialized programming skills. The builder supports enterprise-grade functionality, ensuring reliability and scalability for complex laboratory needs.
The Tetra Data Capture App closes the gap in digitizing data from instruments like balances and pH meters that lack export capabilities. Using advanced photo capture technology, it uploads results directly to records, combining them with metadata for analysis-ready datasets. This ensures no data is lost, enhancing workflow automation across all lab instruments.
Tetra Workflows includes a library of pre-configured recipes for common use cases, supporting integrations with systems like Benchling, Revvity Signals, IDBS, and Veeva Vault LIMS. These recipes enable rapid deployment or customization, leveraging community-driven solutions to save time and resources for laboratories.
Early adopters have seen transformative outcomes: 90% reduction in implementation time, 40% increase in lab productivity, 75% reduction in error rates, and 60% fewer workflow steps. Unlike generic middleware, Tetra Workflows is tailored for scientific data, with deep support for scientific file formats, instrument protocols, and regulations like GxP and 21 CFR Part 11. Its scalable architecture handles the vast data volumes of modern research, ensuring compliance and efficiency.
Tetra Workflows empowers scientists and IT teams by simplifying data access, automating compliance, and reducing IT burdens through self-service tools. Available immediately to existing TetraScience customers at no additional cost, this platform accelerates the adoption of automated workflows, enabling life sciences organizations to focus on advancing human health.
TetraScience is the Scientific Data and AI Cloud company with a mission to improve and extend human life radically. It is accelerating the Scientific AI revolution by designing and industrializing AI-native scientific datasets, which it brings to life in a growing suite of next-generation scientific data and lab data automation products and AI-enabled scientific use cases.
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