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Trusted expertise. Proven data quality.
With over a century of scientific insight, CAS transforms fragmented, inconsistent data into clean, connected knowledge that fuels innovation. Our human-curated content and advanced technology help you unlock the full value of your data, driving breakthroughs in drug discovery, chemical R&D, and manufacturing.


Expertise to integrate AI reliably
AI is only as effective as the data behind it. CAS helps R&D leaders strengthen their data foundation by ensuring both internal and licensed datasets are clean, connected, and ready for advanced applications.
Our expert curation and validation reduce the risk of flawed inputs, so your models deliver insights you can trust with real lasting value.
- Maximize ROI: Ensure your AI investments deliver real value.
- Drive innovation: Accelerate R&D with data you can trust.
- Stay competitive: Use accurate insights to stay ahead of the competition.
Clean, curated data isn’t just helpful—it’s essential for building reliable, high-performing models. Read more in “The importance of data quality in AI applications.”

Data harmonization is essential across industries
Data silos can reduce efficiency and stagnate innovation. You need unified and accessible data to drive progress.
At CAS, we harmonize and integrate your data, making it accessible and actionable. Our solutions ensure your data is standardized and easily searchable, tailored to meet your business needs.
- Biotechnology: Accelerate breakthroughs in genomics, diagnostics, and therapeutic development.
- Pharmaceuticals: Streamline drug discovery and development processes.
- Diversified chemicals: Fuel R&D and ensure regulatory compliance.
- Consumer packaged goods: Illuminate your supply chain and mitigate risks.
Better data means better insights, better decisions, and better efficiency, allowing you to accelerate breakthroughs and stay competitive.
Case study: Faster R&D Insights with CAS Custom Services
Challenge: A health-tech organization struggled to access decades of valuable research buried in unstructured, disconnected systems, leading to repeated work and stalled innovation.
Solution: CAS built a custom knowledge management system that made internal R&D data searchable and scientifically connected, enabling faster insights and more efficient discovery.

"Having clear visibility to what data is already available is critically important. You need to be able to harvest the available information to reduce workload and speed up processes."
How we help
How does CAS ensure data quality?
CAS builds the world’s largest collection of human-curated scientific knowledge covering over 150 years of published science. Our robust collection, curation, and harmonization processes help us build a uniquely comprehensive and connected scientific content collection.
What are the benefits of high-quality data in scientific research?
High-quality data allows researchers to explore vast chemical landscapes, minimize false positives, and focus on top compounds more efficiently. This accelerates the research process and improves the chances of discovering valuable breakthroughs.
Why is data quality important for machine learning?
Quality data is crucial for machine learning because it directly impacts the accuracy and reliability of predictions. Better data leads to better algorithm training, resulting in more accurate and actionable insights.
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