The bottleneck in modern scientific discovery is no longer a lack of human talent. It’s the sheer scale of physical experimentation required. Traditional trial-and-error workflows force brilliant scientists to spend hours manually designing experiments, logging spreadsheets, and waiting on repetitive loops. When developing a new drug takes an average of 10–15 years and costs upwards of $2 billion, every single month of R&D delay matters to patients waiting for life-saving treatments.
To break down these data silos and scale the future of cloud-native, autonomous R&D, Atinary has partnered with Amazon Web Services (AWS). Our code-free agentic AI platform, SDLabs®, has been securely hosted on AWS infrastructure since July 2024. Building on this deep technical integration, Atinary officially became an AWS Partner in September 2025, further validating our commitment to delivering enterprise-grade, cloud-native optimization solutions at scale.
Depending on an organization’s existing laboratory setup, SDLabs® adapts seamlessly to drive value. Whether a team is utilizing our AI platform for smart, data-driven experimental design, or connecting it directly to semi- or fully-automated physical labs, we help industry leaders replace slow manual iterations with continuous, optimized discovery loops.
Proven Real-World Impact
How is our Self-Driving Labs® technology actively shifting innovation from months to weeks?
- Takeda Pharmaceuticals: Accelerated complex bioprocess optimization from months to weeks, achieving an impressive 90% yield in just 3 iterations.
- 📖 Deep Dive: Read more about this use case
- 🎥 On-Demand: Watch the webinar on DMTA innovation
- MIT: Solved a highly complex 5D solar cell optimization challenge in just 33 experiments, successfully meeting a strict 4-week deadline.
- 📖 Deep Dive: Read the Use Case | Explore the Publication
- 💬 Behind the Science: Hear from the Authors on the Impact of SDLabs
Inside the Atinary Self-Driving Labs® in Boston Seaport
In February 2026, the launch of the dedicated Atinary Lab marks a milestone in advancing Physical AI. Engineered to showcase the power of augmenting scientists with AI and robotics, the facility runs continuous, closed-loop Design-Make-Test-Analyze+Learn (DMTA+L) cycles. By anchoring cloud-native orchestration directly to physical automation, this lab serves as an active blueprint for how organizations can reduce manual bottlenecks and drastically accelerate scientific discovery.
Why the Lab of the Future is Cloud-Native and Agentic
By utilizing AWS compute capabilities alongside Atinary’s advanced machine learning optimizers, scientists can navigate billions of possible chemical and parameter combinations. The result? SDLabs® can help generate more high-quality, ML-ready experimental data in a single week than a traditional workflow produces in years, all while keeping proprietary IP completely secure.
The question for life sciences and materials science leaders is no longer if AI belongs in the lab, but how fast your organization can deploy it to deliver results.
Author Contributions
- Original Deep-Dive (AWS Physical AI Blog): Co-authored by Hermann Tribukait (Co-Founder and CEO), Loïc Roch (Co-Founder and CTO), and Martina Löfqvist (Head of Alliances and Strategic Growth) on behalf of Atinary, in collaboration with the AWS Technical Team.
- Website Blog Summary: Adapted by Martina Löfqvist (Head of Alliances and Strategic Growth).