From fragmented data to confident coatings decisions
Compare coating formulations. Evaluate variants. Make data-driven decisions.
In coatings development, new formulations, test values and experimental results are generated every day. Each adjustment generates new data — and without a shared structure, more fragmentation.
LabV consolidates formulations, test values and experimental results in a central data platform. Development teams can then see directly how formulation changes affect adhesion, gloss level or viscosity.
Fragmented data, missing comparability
The data exists, but it is rarely accessible across projects.
What was the gloss level for variant X? Has this formulation already been tested? Which additive has the greatest influence on viscosity? Developers in the paints and coatings industry face these questions every day.
The answers exist, but the data is not accessible: formulations sit in Excel files; test results in PDFs and findings from earlier test series are buried across different projects. Variants are re-tested rather than prioritised on the basis of existing data. The result is lost development time and avoidable repetition.
Integrated data platform for formulation development
All development data in one place.
LabV consolidates coatings formulations, raw material combinations and test data in an integrated data platform. Changes to pigments, binders or additives remain traceable across iterations, as does their influence on material properties such as adhesion, gloss level or viscosity.
Development teams evaluate coating formulations against complete datasets rather than individual test values. Test series are planned more precisely and repeat experiments are reduced as existing findings are directly accessible and comparable.
Develop and document coating formulations in a structured way
Every change to a formulation or process generates new data. To compare it meaningfully across projects, test values, raw material information and experimental results need to be captured together from day one. Pulling distributed data together retrospectively is error-prone and time-consuming.
LabV structures this data so that the relationship between a formulation decision and its test result remains traceable across iterations and development phases. Teams can then compare variants reliably and base decisions on evidence rather than experience alone.
Identify patterns across test series
AI supports the analysis. The team makes the decision. Based on structured data, LabV's AI assistant identifies relationships between formulations and results such as adhesion, gloss level or viscosity, and flags where and why results deviate across test series. Formulations can therefore be prioritised more precisely and repeat experiments reduced.
Formulation development in practice
More structure, less repetition.
A manufacturer of emulsion paints managed several thousand formulations, distributed across different files and projects. After consolidating data onto a single platform, formulation data became connected and searchable across the full development history — enabling systematic variant comparison for the first time. Development teams evaluated coating formulations more precisely, cut repeat experiments and moved faster from existing data to new variants.
Experience live
how formulation data becomes systematically usable.
Experience in a short demo session how LabV brings together formulations, test data and variant knowledge in paint and coatings development.