Atinary launches Self-Driving Labs in Boston, bringing AI into the physical world of R&D
Equipping labs with a frictionless R&D environment where execution, analytics, and learning are natively connected
11 Feb 2026
Atinary, the pioneer of Self-Driving Labs®, has announced that its new AI-powered laboratory will be in Boston, Massachusetts. The new lab marks a critical step in moving AI beyond simulation and software into the physical execution of science, enabling faster, more reliable discovery across chemistry, materials, and pharmaceutical R&D.
The facility houses two autonomous platforms called Atinary’s Scientific Discovery Factories envisioned to continuously design, execute, analyze, and learn from real-world experiments.
By integrating Atinary’s no-code AI platform with robotics and laboratory instrumentation from ABB, Agilent, Bruker, Chemspeed, and METTLER TOLEDO, Atinary augments scientists’ research abilities with AI-driven automation that compounds learning with every experiment for limitless science.
While many AI-first approaches to science focus on prediction or simulation, Atinary operates one level deeper, where hypotheses are physically tested and validated in the lab, data is generated and stored, and learning is compounded with each iteration of experiments.
Experiments are no longer run sequentially or manually. Instead, they execute in closed-loop Design-Make-Test-Analyze-Learn (DMTAL) cycles, with outcomes automatically feeding back into Atinary’s machine-learning algorithms and foundation model to determine the next best experiments.
This AI-native, closed-loop R&D infrastructure enables higher reproducibility and data quality, faster convergence on optimal chemistry and processes, and more efficient use of experimental resources.
Much of experimental science still relies on slow, manual, and expensive trial-and-error. Atinary addresses this bottleneck by combining human scientific judgment with machine-speed screening, execution and learning. This work is guided by Atinary’s multidisciplinary team and Scientific Advisory Board, spanning chemistry, AI, supercomputing, and lab automation, including MIT Professor Stephen Buchwald. Together with its partners, the team advances a model where AI does not replace scientists, but amplifies their imagination, creativity, and decision-making.
The Boston lab initially focuses on small-molecule synthesis and catalysis, supporting pharmaceutical R&D from early discovery through process development, with a platform designed to scale across chemical and materials sciences.
The Self-Driving Lab is delivered as a fully integrated, production-grade platform, combining human intelligence, artificial intelligence, robotics & automation, and precision instrumentation. The result is a frictionless R&D environment where execution, analytics, and learning are natively connected.