Break down data silos. Unlock scientific potential.
CAS helps you eliminate data silos that slow discovery, waste time, and lead to repeated work. By extracting, cleaning, and connecting your fragmented research data across systems, we make it accessible, searchable, and ready to drive faster, smarter innovation.
Unify your data. Unleash your team.
Disconnected data slows progress. When scientists can’t find or trust the information they need, they repeat work, miss insights, and delay breakthroughs.
At CAS, we help you connect the dots. Our experts work with your team to extract, normalize, and harmonize your internal data, no matter the format or source. We help make your data accessible, searchable, and ready to drive results.
- Eliminate redundancy: Stop repeating experiments due to inaccessible data.
- Accelerate discovery: Enable faster, smarter decisions with unified knowledge.
- Maximize ROI: Make the most of your existing research investments.
Are data silos holding you back?
Whether your data lives in handwritten notes, legacy systems, or disconnected ELNs, CAS helps you bring it all together.
Our proven process ensures your data is clean, structured, and ready for AI, regulatory submissions, or next-gen R&D.
- Pharmaceuticals: Connect preclinical, clinical, and regulatory data for faster development.
- Chemicals: Harmonize lab and production data to improve compliance and innovation.
- Consumer packaged goods: Integrate legacy research with modern modeling tools to accelerate discovery.
Case study: Unlocking New Value from Data with CAS Custom Services
Challenge: Toray Industries faced delays in R&D innovation due to unstructured, siloed data and a lack of internal expertise in managing complex scientific information formats.
Solution: CAS partnered with Toray to deliver a tailored training program, equipping scientists with the skills and strategies needed to curate, manage, and apply data effectively across their research efforts.
“This deep understanding of scientific information is a big advantage for CAS.
We have not been able to learn to manage specialized materials data elsewhere.”
How we help
Why are data silos a problem in scientific research?
What makes CAS different?
How does CAS help eliminate data silos?
Can CAS integrate external data, too?
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