Design centrally. Run on restricted compute. Reproduce everything.
Research teams design experiments in one place, then run them wherever the data and compute are allowed to live — often restricted or air-gapped institutional infrastructure. MachineCraft separates design from runtime, so the same experiment moves without a rebuild and every run is on the record.
An experiment you can’t move is an experiment you can’t reproduce.
Institutional compute is rarely where you design. Data-residency rules, restricted clusters, and air-gapped environments keep the runtime locked down — so experiments get rebuilt to fit each environment, and reproducibility erodes with every hand-port. The design and the record drift apart.
One design surface, from whiteboard to restricted cluster.
Design once and the artifact carries everything it needs to run elsewhere — and to leave a complete record of how every result was produced.
Design centrally
Compose experiments visually from 100+ components across 22 model integrations — a visual builder with code extensibility, so your team standardizes on one design surface instead of bespoke scripts.
Run on restricted compute
Every workflow is a portable artifact. Ship the same design to institutional clusters, on-prem GPUs, or fully air-gapped compute — env-var differences only, with no connection back to the design environment.
Reproduce everything
Every run writes a complete record — decisions, state transitions, credential and external-service access. The audit trail that satisfies compliance is the same record that makes a result reproducible.
Research agents are in beta. Multi-step reasoning agents are functional and demoable; the Workflow Engine, deploy-anywhere, and audit trail ship today. See how the platform works
Designed in the lab, run where the data lives.
A research institution designs its pipelines centrally, then executes them on restricted institutional compute — with a full record of every run, so results hold up to scrutiny and can be reproduced from the record.
Reproducibility as a byproduct of governance
The same audit trail that lets a regulated enterprise prove what an agent did lets a research team show exactly how a result was produced — same inputs, same steps, same record. Governance and reproducibility turn out to be the same problem.
Design once. Run anywhere your data is allowed to live.
Join the private beta, or talk to our team about restricted-compute and air-gapped deployments.