Visual Workflows
for
Scientific
Computing

A polished desktop experience on macOS, Linux, and Windows. No server to configure, no browser tabs to manage — download, launch, and start building workflows.

Build computational pipelines by dragging nodes onto a canvas and connecting them visually. What Nextflow and Snakemake require in DSL code, Salpa does with drag and drop — accessible to every scientist, not just programmers.

Stay in pure Python. Write your logic in core.py, define inputs in node.py — and your script becomes a visual node with an auto-generated UI panel. No framework to learn, no server to build, no XML definitions.

Run locally by default. When jobs need GPU power or environments are hard to deploy, dispatch to cloud nodes — or submit to your institution’s HPC cluster. One interface for every execution target, with real-time progress tracking.

Your data stays on your machine — always. When you opt into cloud computing, jobs run in isolated, ephemeral containers with no data retention. Full control over sensitive research data.

Every node runs in its own isolated environment. Install a node and its dependencies resolve automatically — no pip conflicts, no Docker required, no manual setup.

Browse, install, and publish community nodes through an open marketplace. Load node sources directly from GitHub or local folders — no lock-in, no gatekeeping.

Export any workflow as a self-contained project. Share with colleagues and they reproduce your results with one click — no tribal knowledge, no environment guesswork.

Molecular dynamics, structure prediction, docking, and more — shipped as ready-to-use nodes in the app. We’re continuously developing new nodes for molecular modeling and life science, so your toolbox grows with every update.