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Read first principles insights on Scientific AI, and how we're reimagining and replatforming science for the era of AI.

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Tetra Data is the atomic building block of Scientific AI

Transforming your scientific data — currently trapped in vendor silos and in proprietary and/or unstructured formats — into your most valuable corporate asset: AI-native data.

What is Tetra Data?

Tetra Data is your fully transformed data and the atomic building block of Scientific AI.

Tetra Data is designed and manufactured in the Tetra Scientific Data and AI Cloud via a highly sophisticated data engineering process in which raw scientific data is transformed into the customer's AI-native data.

This scientific data industrialization process transforms static, subscale, proprietary, and/or unstructured data contained in vendor-specific silos, into liquid, large-scale, engineered, and compliant data.

AI-native Tetra Data — comprising scientific taxonomies and ontologies — revolutionizes lab management, scientific use cases, CMC, and biopharma and CxO collaboration.

Transform raw data into
AI-native data

Raw data

Vendor-specific
No AI utility

Vendor silos represent a subset of customer data, inhibiting scale

Vendor-specific formats and/or unstructured data limit data engineering

Vendor silos, raw data, and legacy stacks limit data liquidity

Vendor data silos serve as structural impediments to Scientific AI

Replatformed data

Centralized in the cloud
Precondition for data engineering

Liberated from silos, now unified in the cloud

Compliant, traceable, with full data integrity

Contextualized for scientific use cases

Includes meaningful, AI-relevant metadata

Engineered data

Sophisticated data engineering
AI-native data
AKA Tetra Data

Transformed into a harmonized, open, vendor-agnostic format

Sophisticated scientific taxonomy and ontology design

Contextualized to enable real world scientific use cases

Industrialized scientific data at scale as a foundation for Scientific AI

Tetra X Data

Shareable and extensible
Fuels data scale, liquidity, and context

Collaborative and extensible AI-native scientific data

Shareable across CROs, CDMOs, and other critical partners

Unprecedented data liquidity fuels even greater data scale

Liquid and collaborative AI-native data yields transformational outcomes

Tetra AI

Scientific expertise
Data engineering
AI

The world's only open, purpose-built, and collaborative scientific data and AI cloud

Uniquely combining deep expertise in science, data engineering, and AI

End-to-end scientific data workflows spanning scientific use cases and modern data and AI stacks

Industrializing large-scale, liquid, engineered, and compliant scientific datasets combined with AI to produce transformational outcomes

Explore resources

Learn how to transform your scientific data into AI-based outcomes.

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By transforming how our scientists access, analyze, and share research data, we're unlocking new levels of productivity and enabling AI-powered insights through a connected, online data environment. Beyond boosting productivity, we're leveraging data and agentic AI to accelerate innovation across our drug discovery engine.

Jim Villa
Global Head of Research Strategy & Operations

Our expanded partnership with TetraScience is delivering measurable value through unified access to instrument and CRO data that powers our automation and analytics at scale. The platform's audit capabilities have streamlined our regulatory preparation processes.

Linus Goerlitz
Regulatory Science Transformation Lead

Embedding AI and digital technologies across the R&D value chain is one of Takeda’s core strategic areas for our future. Our data-driven R&D approach will reduce discovery timelines, enable the identification of targets faster, and help us design better therapeutic candidates.

Nicole Glazer
Head of R&D Data, Digital and Technology