Atinary, a World Economic Forum 2026 Technology Pioneer, enables Self-Driving Labs that combine AI, robotics, and human expertise to accelerate scientific workflows in pharmaceuticals, chemicals, energy, and materials.
Self-Driving Labs represent the next frontier: physical AI in R&D labs. Think of them as “Waymos for science,” says CEO Dr. Hermann Tribukait, who co-founded the company with CTO Dr. Loïc Roch, a quantum chemist and expert in AI/ML for materials discovery, software design, and autonomous experimentation.
“Our vision at Atinary is augment, not replace, scientists with AI and robotics, freeing them from tedious and error-prone tasks to spend most of their time on what matters most: focus on science with creativity, reasoning, and imagination,” says Tribukait, an economist, entrepreneur, and expert in innovation and technology development. “This is how we can solve the bigger problems across health, energy, materials, and sustainability. “
Self-Driving Labs do not need to wait for world models—platforms built on an understanding of the physical world. (see The Innovator article on the evolution of world models). Instead, they design, run and learn from real-world chemistry and materials experiments in a closed loop, “Our algorithms learn the ground truth from the lab experiments,” says Tribukait. “They are data driven. What is more important: curing cancer or finding out why an algorithm worked? We need this fast and we can get there faster by letting the data drive us there.”
Atinary says its Self-Driving Labs can generate as much data in five days as a PhD does in five years.
“I would argue that the biggest impact of physical AI in the lab is that it will allow scientists to run experiments that would otherwise be too expensive and too hard. It will make the impossible possible,” says Tribukait.
The name Atinary comes from the Spanish verb atinar, which means “hit,” as in hit the target. The company says its leading AI agentic platform, SDLabs, and machine learning (ML) technology can hit targets ten to a thousand times faster than standard methods used in industry and academia, such as Design of Experiments (DoE) and One-Factor-At-A-Time (OFAT).
Atinary, which splits its headquarters between Lausanne and Menlo Park, California, is one of the field’s original players — founded in 2019, the founders coined the term “Self-Driving Labs” back in 2017, well before current advances in AI and large language models. The Atinary Lab inaugurated in Boston this year integrates Atinary’s code-free AI/optimization platform with robotics and instrumentation from ABB, Agilent, Bruker, Chemspeed, and Mettler-Toledo. Its pitch is a hardware-agnostic and workflow-agnostic “brain layer” that enables a closed-loop Design-Make-Test-Analyze-Learn optimization cycle that can bolt onto existing lab equipment at the clients’ labs rather than owning the hardware stack itself. “A chemist with no experience in AI can deploy in the existing workflows in two hours,” says Tribukait.
The company is closely collaborating with ETH Zürich, MIT, and other leading universities. The Swiss university is using Atinary’s technology to run three automated labs in Zürich, and Atinary is using the university’s labs to come up with new catalysts. The head of the ETH Zürich Catalysis Hub — Dr. Paco Laveille — is on Atinary’s scientific advisory board.
Publicly disclosed customers include Takeda Pharmaceuticals and dsm-firmenich, among other leading companies in pharma, chemicals, energy, and food.
Several weeks ago, Atinary said it helped a new top pharmaceutical company client find a new reagent candidate that was higher performing and greener. “The positive results surprised their chemists,” says Tribukait. “They said they would have never thought of this. We are getting this kind of result today. Imagine what we will be able to do five years from now.”
In addition to pharma and specialty chemicals, Self-Driving Labs can play a crucial role in aiding the energy transition, says Tribukait, a scheduled speaker at the World Economic Forum’s Sept. 16 Energy Forum in Geneva. “Materials discovery in energy materials will be crucial for everything from making better batteries — with higher energy density and lower weight — to higher-efficiency solar cells, and catalysts that convert CO2 to fuels, among other key energy and climate technology solutions.”
An Increasingly Crowded Field
Atinary is not the only company developing Self-Driving Labs. “It has become a thing, everybody is now jumping on the bandwagon, which is great,” says Tribukait.
Competitors include heavily funded “AI science factory” challengers such as Lila Sciences, which has raised $550 million and is backed by Nvidia’s venture arm; Emerald Cloud Lab, a labs-as-a-service company with a decade-plus operating history of automated labs that added AI in 2023 and has partnerships with universities such as Carnegie Mellon; Ginkgo Bioworks Cloud Lab, which offers synthetic biology automation and has a collaboration agreement with OpenAI on closed-loop experimentation; as well as early- to growth-stage materials informatics and AI orchestration platforms like Citrine Informatics, which are also hardware- and model-agnostic.
Tribukait says its differentiators include:
- Pioneering Team: Atinary’s multidisciplinary team has been working on Self-Driving Labs for almost 10 years, building the platform SDLabs from scratch. One of Atinary’s advisors is Massachusetts Institute of Technology Prof. Stephen Buchwald, co-author of over 550 published papers, holder of 55 issued patents, and one of the most cited chemists in the world. “He is not only a figurehead, he works hand in hand with us in our Boston lab to optimize reactions he has discovered,” Tribukait says.
- Ecosystem: Many of the players in the self-driving lab space are new or have only been in the market for a few years. “We have been building a deep ecosystem in industry and academia over the last ten years which includes some of the largest leading robotics and lab instruments companies,” says Tribukait. “We have strong partnerships with all of them.”
- Flexibility: Atinary partners with the top hardware manufacturers so that “the customer can use whatever is best for them.” Plus, robots are not a must. They can be an add-on. “We meet the customer where they are,” he says. “Most of our clients are hesitant to invest in CAPEX at the beginning. They start using our platform SDLabs by integrating AI into their existing workflows and work with them to add robotics when they are ready.”
- Results: Unlike many newcomers, Atinary says it has published results with industry and academic leaders in peer-reviewed scientific journals, such as ACS Catalysis, as well as in webinars with companies like Takeda Pharmaceuticals.
