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Elarix is the AI co-scientist for materials R&D. It reads thousands of papers and your lab data, connects them into a physics-aware knowledge graph, and reasons over it to recommend the next experiment worth running.
Elarix structures the world's materials science — literature, lab data, simulations — into one physics-aware graph, then applies AI reasoning to plan experiments. Every recommendation comes with a source for every claim.
Elarix's AI reads thousands of scattered papers and internal runs and normalizes them into Composition → Process → Property — one queryable base where every link is traceable to its source.
Instead of screening fifteen options, the co-scientist reasons over the graph and puts the two or three highest-confidence next steps in front of you — with predicted gain and the evidence behind each one.
AI-guided molecular-dynamics and DFT simulation screens candidate materials computationally before anything reaches the bench — physics-aware, and every result stays traceable.
Built on DLR-proven AI and materials science, by a team that has lived the R&D bottleneck.
Starting in the sustainable polymers sector.
Partnering with academia to train global AI materials models.