Computational Chemistry
Molecular dynamics simulations. Drug discovery pipelines. Materials science modeling.
(screenshot)
RESEARCH & ACADEMIA
Universities, national labs, and research institutions need computational environments that enable collaboration without compromising data governance or intellectual property.
THE CHALLENGE
Every PhD student spinning up their own Python environment. Postdocs with API keys in plaintext. No audit trail on who accessed what data. Grants requiring data governance you can’t demonstrate.
Real solutions for real research challenges.
Multi-tenant isolation — Each lab group gets their own environment. No cross-contamination.
Grant compliance — Demonstrate data governance for NIH, NSF, DOE, and international funders.
AI-assisted analysis — Turn your average researcher into a 10x data scientist. Natural language to SQL. Instant visualizations.
Reproducible environments — Same environment, every time. No more 'works on my machine.'
Collaboration without compromise — Share notebooks, not credentials. Collaborate without exposing raw data.
Any data source — Connect to institutional databases, cloud storage, APIs. Query anything, build any report.
THE AI LAB
Hook it up to your data. Ask questions in plain English. Get answers.
Your researchers become more productive. Your compliance posture improves. Everyone wins.
Molecular dynamics simulations. Drug discovery pipelines. Materials science modeling.
Signal processing. Simulation data analysis. Instrumentation control.
Sequence analysis. Gene expression studies. Population genetics.
Climate modeling. Satellite data processing. Environmental monitoring.
Survey analysis. Behavioral data. Policy research.
Text analysis. Corpus linguistics. Historical data digitization.