The digital transformation journey can be a bumpy road. Data silos, a heterogeneous software ecosystem, and complex scientific data and workflows introduce risk and costs.
Optimize your data strategy with a trusted and proven industry data and AI cloud leader.
Replace dead-end DIY approaches with a secure, end-to-end architecture that drives high-impact outcomes
Eliminate silos enterprise-wide and create a single source of truth for all your scientific data
Democratize AI and create smart capabilities that put the power of AI and analytics into the hands of employees
Leverage industry best practices to mitigate risks and lower the total cost of ownership
Identify and resolve major bottlenecks in scientific data workflows with Tetra Catalysts
Boost data workflow efficiency by orders of magnitude in R&D, QA/QC, and manufacturing
Maximize platform use to harness all your scientific data and stay agile in a dynamic business environment
Future-proof all your scientific data for reuse by transforming it into AI-native Tetra Data
Enable stakeholders to build large-scale, liquid datasets for strategic decision making
Find out what you need to embark on your AI journey and how to reach your goals faster.
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
