Scinetics

Based in China, Scinetics, operates as a developer of AI (Artificial Intelligence) infrastructure for scientific research. Based in Shanghai, China and founded in 2026, Scinetics, develops AI infrastructure for scientific research. The funding will be used for the iteration of AI4S foundational scientific models, the large-scale deployment of automated experimental platforms, and the expansion of the core team. Scinetics offers a suite of advanced products specializing in the integration of artificial intelligence with scientific research, enabling a continuous loop of hypothesis, design, validation, and evolution.

Key offerings include an AI4S foundation model that connects to autonomous laboratories, facilitating self-evolving AI scientist systems, and generative models for RNA and protein design. These products serve a diverse range of sectors, including life sciences, materials science, quantum physics, aerospace, and chip design, with applications for both research institutions and commercial enterprises. Scinetics targets markets primarily in North America, Europe, and Asia, providing innovative solutions to scientists looking for automated and efficient methods for experimental discovery. Their tools are designed to support high-level research activities, allowing teams to make rapid advancements within their respective scientific domains.

The revenue model for Scinetics revolves around partnerships and subscriptions tailored for a B2B clientele. Typically, clients, such as research institutions, pharmaceutical companies, and biotech firms, engage with Scinetics to integrate their AI systems and laboratory automation tools into existing research frameworks. These transactions often involve annual or multi-year subscription agreements, ensuring ongoing support and updates for the software and systems utilized. Additionally, proprietary offerings such as Stella, LabOS, PocketGen, RNAGenesis, BioMiner, and ATOMICA are integral to their business structure.

Clients benefit from tiered pricing plans associated with these products, which afford scalable options based on the specific needs and scale of the institution’s research operations. The company plans to iterate on AI4S foundational scientific models, deploy automated experimental platforms on a large scale, and expand its core team.