Gumloop vs Runner

Gumloop and Runner are both workflow automation tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

Gumloop

Gumloop lets growth, sales, and ops teams wire together multi-step AI agents that run on their own — pulling from external APIs, enriching CRM records, drafting content, and firing results into Slack or Teams without a human trigger per run. The visual builder handles the common cases well: lead enrichment, meeting prep, competitive research. Branching logic that depends on what a previous step returned is where the ceiling appears — complex conditional paths push teams toward adding custom code nodes, which means they are now maintaining two layers. Security and compliance teams get enterprise-grade controls over AI usage, which matters when rolling out to non-technical employees at scale.

Runner

Runner connects to 50+ apps and executes tasks across them — pulling context from email, calendar, chat, and cloud files, then acting on what it finds rather than handing the work back to you. The built-in Chrome browser fires up in the background to unblock searches without interrupting what you're doing, and a permission layer lets you sign off on each action until you're comfortable letting it run faster. Memory accumulates across sessions, so the tool builds a model of how you work over time. The ceiling appears when you need custom conditional logic or integrations outside the supported app list — there's no API to extend it yourself, and no self-hosted option if your data governance policy requires it.

Attribute	Gumloop	Runner
Pricing	Paid	Paid
Price	$37/month	$50/month
Free trial	No	7 days
Open source	No	No
Has API	Yes	No
Self-hosted option	Yes	No
Platforms	Web-based platform with Slack, Microsoft Teams, and email integrations	Desktop app with web connections
Released	2023	—
Pros	Autonomous agent execution without a human trigger per run, which means a prospecting workflow can enrich and qualify leads overnight and surface results in Slack by morning without anyone managing it. Provider-agnostic AI model calls inside the canvas, so swapping the underlying model when costs shift or a better option appears does not require rebuilding the workflow. Native Slack and Teams integration at the agent output layer, which means results land where the team already works instead of requiring a separate app check that gets ignored. Self-hosted deployment option, so teams with data residency or compliance requirements can run agents without sending sensitive CRM or customer data to external infrastructure. Non-technical employees can build and modify agents without engineering support, which means ops and marketing teams ship automations without waiting in a sprint queue.	Executes across 50+ connected apps in a single session, so you stop context-switching between tools to assemble the information a task actually requires. Built-in browser automation runs in the background, which means tasks that hit a dead end in a direct integration — venue research, public data lookups — resolve without handing the work back to you. Permission controls let you stay in the loop on every action before Runner takes it, so early adoption doesn't require trusting a black box with your calendar or CRM. Session memory accumulates preferences, contacts, and tool patterns over time, so recurring tasks like weekly exec handoffs stop requiring the same setup instructions each time. Lead enrichment and follow-up drafting happen at the moment a form submission arrives, which means inbound leads don't sit cold while a rep manually pulls context before the first reply.
Cons	Conditional branching based on what a prior step returned hits the visual model's practical ceiling around the third or fourth branch — teams handling complex qualification logic or multi-path enrichment add code nodes to compensate, at which point they are debugging two systems instead of one. Agents that need to maintain state across sessions or resume from a mid-pipeline failure require workarounds the canvas does not natively express — teams with reliability-critical pipelines where a failed API call must retry with context intact end up moving those flows to code-first orchestration tools. The free tier caps usage at a fixed monthly credit ceiling, which means any team running high-frequency agents — hourly CRM syncs, real-time lead enrichment at volume — hits the limit quickly and must upgrade or throttle the workflows they just built.	No API and no self-hosted option mean any integration outside the 50-app catalog is a dead end — teams whose stack includes internal tools or niche SaaS products hit this wall immediately and route those workflows elsewhere. Complex conditional logic — branch on what the last step returned, handle exceptions differently by account type — has no visual or scriptable layer to build it on. Teams with that requirement move to a programmable automation platform and maintain Runner only for the simpler personal-productivity layer. The permission model, while useful early on, adds friction at volume. High-frequency tasks like real-time lead routing require reducing those checkpoints, which shifts risk to users who may not fully understand what Runner will do when unsupervised.

Bottom line

Only Gumloop exposes a public API. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Gumloop and Runner?

Gumloop is Paid, while Runner is Paid. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Gumloop better than Runner?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.