Sim-to-Lab intelligence for materials R&D
Deciding the next experiment with AI, simulation, and lab feedback.
Cloud-native SaaS — sign in and run from any browser, no installation required.
Lymeric builds AI- and physics-based systems that help materials R&D teams decide what to try next: the next candidate, condition, measurement, or validation path.
Our philosophy is Sim-to-Lab: virtual scientific worlds provide dense evidence, while real labs provide sparse but decisive feedback. We turn both successful and failed experiments into a continuously improving R&D policy engine.
Why Sim-to-Lab
Materials R&D needs adaptive experiment policies
Traditional AI screening often ranks a large candidate set, then hands a short list to the lab. In practice, teams must also weigh cost, process constraints, uncertainty, information value, and risk before choosing the next experiment.
Lymeric treats each loop as a decision problem. Simulation, literature, prior data, and lab outcomes are organized into a belief state that helps researchers reduce uncertainty and choose the next action with clearer evidence.
Approach
A closed loop from target to lab feedback
We start from target performance and constraints, build a materials world model, propose the next experiment, then update the policy with real lab results including failures.
Virtual scientific worlds
DFT / MD / MLIP / QSPR
Experiment policy
Uncertainty and constraints
Real lab alignment
Results and failures
Products
Two product lines across materials and research workflows.
All product lines run as web services on scalable cloud infrastructure and are delivered as SaaS subscriptions — sign in from a browser and start working immediately.
Battery materials
Battery Intelligence
Decision-support workflows for battery materials R&D, including cathode materials and solid electrolytes.
Research knowledge workspace
MashNote
View MashNoteAn AI-native research note and knowledge workspace for capturing, structuring, and reusing technical work.
Common product philosophy
Each product connects domain knowledge, model output, and user feedback into a practical R&D loop.
Product in action
Real workflows, running in the browser.
Pricing
Plans that scale with your R&D team.
Pilot
For a first scoped decision loop on one materials problem.
- Browser-based workspace for one project team
- Managed cloud compute for simulation workloads
- Onboarding with our science team
- Email support
Team
RecommendedFor R&D teams running continuous Sim-to-Lab loops.
- Everything in Pilot
- Multiple projects and shared knowledge base
- Priority compute queues and larger model budgets
- Integrations with lab data sources
- Priority support
Enterprise
For organizations deploying across departments.
- Everything in Team
- SSO and enterprise security review
- Dedicated environments and data residency options
- Custom model development and on-site workshops
- Dedicated success manager
Pricing is tailored to pilot scope and team size — reach out for a quote.
Team
Built across AI, chemistry, physics, and material science.
Core team
Experimental chemistry, biochemistry, and R&D process design; translating technical research problems into product and business strategy.
Ph.D. Chemistry, Columbia University; B.S. Chemistry, KAIST; former IQVIA consultant and National Cancer Center researcher.
Large-scale models, reinforcement learning, graph neural networks, and physics-based modeling for structured scientific and materials data.
Ph.D. Physics, UC Berkeley; B.A. Physics/Math, Cornell University; former chief scientist at Bone, with research experience at CERN and Oxford.
Contributors and advisors
Contributors
Chief Engineer : Computational chemistry, and AI-enabled research workflows. Joining full-time later this year. Other contributors include AI scientists and material engineers.
Advisory network
Scientific advisors across AI, computational chemistry, materials science, software engineering, and industrial R&D.
Partner with us
Selective pilots for Sim-to-Lab workflows
At this stage, we are discussing focused pilots where simulation, existing data, and lab results can be connected into a measurable decision loop. Reach out for more information.
contact@lymeric.ai