01. Hypothesis
We frame testable questions, map assumptions, and define failure criteria before analysis begins.
Independent Nonprofit Computational Research Lab
Santaros Labs studies how scientists and AI can reason, write code, analyze evidence, and build knowledge together—without losing rigor, provenance, or human judgment.
MISSION
Santaros Labs is a nonprofit research organization focused on the methods of AI-assisted science. We study how evidence is gathered, transformed, checked, and communicated across the full research workflow.
We frame testable questions, map assumptions, and define failure criteria before analysis begins.
We build traceable AI-assisted workflows for literature, code, modeling, and data analysis.
We test reliability with blinded checks, replication, audit trails, and clearly reported limitations.
Testing where AI expands hypothesis generation—and where it introduces confident error.
Designing research workflows that another scientist can inspect, rerun, and challenge.
Studying shared AI workspaces, handoffs, provenance, and collective scientific judgment.
Measuring citation fidelity, uncertainty calibration, contradiction handling, and error detection.
EVIDENCE INTEGRITY
We separate proposed work from completed work, publish methods before outcomes when feasible, and preserve the chain from source material to code, result, interpretation, and limitation.
Preregistration-ready protocols
Reproducible computational workflows
Mixed-method evaluation
Transparent limitations
Cross-disciplinary collaboration
SUPPORT OUR WORK
Santaros Labs welcomes grants, philanthropic support, compute credits, data partnerships, and scientific collaborators for reproducibility and human–AI research.
PARTNER WITH US
Santaros Labs welcomes principal investigators, research groups, nonprofit institutes, funders, and technical partners who want AI-assisted science to be inspectable, reproducible, and useful.