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Velaris vs Gumloop
Node graphs for AI work vs. delegation with no graph at all.
Gumloop puts AI inside a node canvas — chain a scrape, an LLM call, a sheet write, run it on a schedule — and it is a clean take on that idea. Velaris removes the canvas: you describe the outcome, and a LangGraph agent picks the tools and the order itself, checking in with you before anything destructive.
| Capability | Velaris | Gumloop |
|---|---|---|
| The building surface | A sentence — no graph to draw | A node canvas you wire by hand |
| Choosing the steps | The agent plans them at run time | You fix the path at build time |
| Connector reach | 1000+ via a searchable capability mesh | Built-in nodes plus custom code |
| Approvals | Read auto, write logged, destructive needs a tap | Approval nodes you place yourself |
| Where it lives | A browser desktop, plus Telegram | A web workflow builder |
When Gumloop is the better choice
When you want to see the pipeline — a scrape, an enrichment, a sheet write that runs nightly and must do the same thing every time — a Gumloop graph is inspectable, debuggable, and easy to hand to a teammate.
See what an AI OS feels like
Join the waitlist and be first in when Velaris opens up.