Komos vs Gumloop
Gumloop is an AI automation builder with visual flows. Komos is an AI coworker platform where Moss builds, runs, and maintains the work across browsers, documents, and integrations.
Gumloop and Komos both help teams automate complex work with AI. The difference is ownership. Gumloop gives teams a visual flow builder with AI powered nodes. Komos gives teams Moss, an embedded AI engineer that can build from a recorded demo or a plain English request, run the workflow in a managed sandbox, and adapt when a portal or API changes. Gumloop is strongest when an operator wants to assemble a flow directly. Komos is strongest when the team wants the repetitive work handled end to end, including browser steps, documents, credentials, schedules, and run history.
| Feature | Komos | Gumloop |
|---|---|---|
| Primary model | Moss builds and maintains workflows from demos or chat | Users assemble visual AI flows with modular nodes |
| Browser heavy workflows | Native managed browser sandbox for portals and websites | Useful for web data and workflow steps, but less focused on operated browser sessions |
| Workflow maintenance | Moss can diagnose failures and adapt selectors, prompts, and steps | The flow owner edits the canvas when the process changes |
| Learning from demonstration | Record the work once and turn it into a reusable task | Build the flow from nodes, prompts, and connectors |
| Operational audit trail | Step logs, screenshots, files, and replayable run history | Run visibility depends on the flow and workspace setup |
| Best fit | Recurring operations where the team wants the work delegated | Teams that want hands on control of an AI flow canvas |
- The workflow includes websites, portals, documents, credentials, and integrations in one process
- You want an AI engineer to build and change the workflow, not just a canvas to edit
- The process runs repeatedly and needs logs, screenshots, retries, and ownership across a team
- Your team records the current process better than it can design a node graph from scratch
- You need automation that can survive changes in the websites it operates
- Your team likes building directly on a visual AI workflow canvas
- The work is mostly data movement, enrichment, and AI reasoning inside a flow
- You want operators to manually tune each node and prompt
- Browser operation and credentialed portals are not central to the workflow
See Komos run the work, not just describe it
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