Solutions — research teams
Reproducibility, cost control, and collaboration for AI research. Build agents that advance the frontier — without the infrastructure overhead.
[ 01 ]Built for the lab
Reproducible experiments
Every agent run produces a deterministic execution graph. Replay any experiment, branch from any node, share with collaborators. No more 'it worked on my machine.'
Cost-efficient compute
Multi-model routing sends complex reasoning to frontier models and routine tasks to smaller ones. Cut inference spend by 60% without sacrificing quality.
Collaborative agent design
Shared workspaces, version-controlled prompts, and built-in evaluation. Your whole team can iterate on agent behavior simultaneously.
Publication-ready outputs
Quality scoring and drift detection ensure your agents produce consistent, reproducible results. Attach execution graphs as supplementary material.
[ a ]inference spend cut by routing
[ b ]execution graph per agent run
[ c ]re-runs needed to reproduce
[ 02 ]The point
Focus on the science. mynd handles the infrastructure, observability, and cost management.