Replacing a legacy electronic laboratory notebook (ELN) was only the starting point for Clariant. The broader goal was to create a structured, connected scientific data foundation that links chemical synthesis, formulation development, testing, and commercial requests across a global R&D organization.
Working with Uncountable, Clariant has expanded its deployment from 600 to more than 1,000 users across 35+ global sites. The platform now supports a more consistent way to document, find, share, and reuse experimental knowledge, while laying the groundwork for advanced analytics and AI-enabled innovation.
Moving beyond “paper on glass”
Clariant’s previous ELN digitized laboratory records but did not provide the flexibility or momentum required by a modern R&D organization. Changes could take years to implement, leaving scientists to rely on workarounds and making it difficult for the system to evolve alongside the needs of the laboratory.
The company needed more than a replacement for paper records. It needed a scientific backbone that could connect synthesis teams with application teams, support both structured and flexible experimental workflows, and scale across geographies and business units. The result needed to make data easier to capture, search, share, and use, not simply store it electronically.
One platform for different ways of working
Clariant’s R&D teams work across both chemical synthesis and formulation development. Those disciplines generate different types of experimental information: synthesis workflows can require detailed process parameters, while formulation teams may need to compare complex combinations of ingredients, concentrations, properties, and test results.
Uncountable enabled Clariant to develop templates tailored to the practical needs of different laboratory teams while maintaining the structure needed for reliable data management. Scientists can choose the information they need to see during planning, execution, and documentation, helping make the system useful in day-to-day work rather than an additional administrative step.
This balance between standardization and local flexibility was particularly important for a global rollout. Clariant established common elements for its worldwide user base while configuring workflows around the needs of individual organizations, helping support acceptance across regions and functions.
Connecting commercial, laboratory, and analytical workflows
The value of a connected data foundation extends beyond the individual experiment. Clariant has brought its commercial organization into the workflow, enabling sales teams to submit customer-driven laboratory requests directly through the platform. That creates a faster path from customer need to technical action and improves communication between commercial and R&D teams.
The company has also integrated its ELN with a laboratory information management system (LIMS). Laboratory users can submit test requests to analytical teams and receive results back in the ELN, keeping experimental context and analytical outcomes connected without relying on manual handoffs or disconnected records.
As more work is captured in a common environment, scientists can also search prior experiments and results before beginning a new project. This makes it easier to build on existing knowledge, identify relevant past work, and reduce avoidable duplication in formulation or synthesis activity.
Delivering adoption at global scale
After a competitive evaluation in 2023, Clariant selected Uncountable based on its flexibility and its ability to adapt to the company’s requirements. The subsequent rollout was ambitious: more than 800 people were onboarded in less than 10 months, supported by committed power users, executive sponsorship, IT support, project management, and departmental leadership.
Clariant transferred approximately 500,000 data points and their attachments, trained former users, and expanded the total user base from 600 to more than 1,000 colleagues globally. Initial feedback showed that users found the new platform more intuitive than the previous system, while monthly ELN usage reached 70%, approximately double the adoption rate achieved with the legacy system.
Creating an AI-ready R&D ecosystem
For Clariant, the most significant opportunity lies ahead. AI can improve individual productivity, but its strategic value increases when it can be applied to an organization’s proprietary scientific knowledge. That requires accessible, consistent, and well-structured experimental and analytical data.
By capturing data in a structured digital environment, Clariant is building the foundation to use its scientific knowledge more effectively. Its next priorities include visualization, predictive modeling, broader data integration, and continued development of AI-enabled capabilities. The aim is to give scientists faster access to insights and help R&D teams make better-informed decisions from the data they generate every day.
The ELN rollout is therefore not the end state. It is the first step in creating a connected R&D ecosystem; one that links data across the innovation process and gives Clariant a stronger platform for accelerating development and delivering value to customers.
This article draws on Clariant’s customer case study video with Uncountable, in which leaders from both organizations discuss replacing a legacy ELN, connecting R&D workflows, and building a structured data foundation for analytics and AI. Watch the original case study here.
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