DP Technology is a Beijing-based AI for Science company founded in 2018, with offices and R&D centers in Beijing, Shanghai, Shenzhen, and Yibin. The company focuses on using AI to accelerate scientific discovery and industrial R&D, with a mission centered on building intelligent scientific systems and eventually “AI Scientists” capable of assisting or automating parts of research workflows.

Its positioning is distinct from consumer AI platforms because it combines scientific foundation models, simulation infrastructure, and domain-specific research tools for use in life sciences, materials science, energy, and computational research.

Main products and services

• Bohrium scientific research platform
  DP Technology’s Bohrium platform is presented as a scientific research space and computing environment that supports reading, computing, experimenting, and research collaboration across modern scientific workflows. Public descriptions also refer to Bohrium as a cloud-based research platform and asset hub within the company’s broader AI-for-science ecosystem.

• Scientific foundation models and agents
  The company has developed the Particle Universe scientific discovery engine and related pre-trained science models, alongside SciMaster, described publicly as a general-purpose scientific AI agent. These products are designed to bridge scientific knowledge, computation, and research assistance in complex technical domains.

• Industry-specific R&D platforms
  DP Technology also offers specialist platforms such as Hermite for computational drug design, RiDYMO for dynamics and hit discovery, Piloteye for battery design automation, Uni-Lab for laboratory workflows, and Lebesgue Intelligent Computing for computing orchestration. Together, these tools target practical use cases in drug discovery, energy, material science, and industrial research.

Key advantages

• Clear leadership in AI for Science
  DP Technology is publicly positioned as a leading company in the AI-for-Science paradigm, which gives it a distinctive niche compared with general-purpose LLM or application-layer AI firms.

• Full-stack scientific R&D ecosystem
  Its product suite spans scientific models, computing infrastructure, lab systems, and vertical research applications, which makes it more than a single-product AI startup. This full-stack structure is especially valuable in scientific and industrial settings where workflows are fragmented across simulation, experimentation, and decision-making.

• Strong industrial application potential
  Public materials show deployment across drug discovery, battery design, materials science, and broader scientific computing, indicating that the company’s platform is designed for real research and industrial use rather than only academic experimentation