Dust vs Gumloop
Gumloop scores 7.3 to Dust's 5.7 among the AI agent builders we rate, and is the better pick for 4 of the 4 kinds of buyer below.
Gumloop wins, 7.3 to 5.7
Dust has a free plan that never expires, though its 500 credits are a one-time allocation rather than a monthly refresh; Gumloop has no free plan, only a 14-day trial that rolls into a paid Pro subscription. Dust builds agents through a step-by-step form guided by an AI copilot rather than a visual canvas, while Gumloop keeps a drag-and-drop builder. Gumloop connects to a stated 250 apps against Dust's 20, and Gumloop costs $37 a month against Dust's $32.4 a month.
Pick Dust if you want a free plan and don't need a visual canvas.
Pick Gumloop if you want a visual drag-and-drop builder and more app connectors.
Best for
Who each one suits, decided on the criteria that matter to that buyer and the checked facts where the two differ.
- Visual builder: Gumloop yes, Dust no
- But Dust leads on free plan: Dust yes, Gumloop no
- App connectors: 250 apps against 20 apps
- BYOK: bring your own model or key: Gumloop yes, Dust does not say
- Test and evaluate agents: Gumloop yes, Dust does not say
- Self-hosted edition: Gumloop yes, Dust does not say
How they score
Both are scored the same way, against the other AI agent builders we rate, from facts on each vendor's own pages. Gumloop leads on 4 of 7 criteria.
Where they differ
Every point where the two vendors' published facts disagree, with a link to where each fact was read. "Not published" means the vendor does not say either way.
Published by only one of them
Where they match (7)
Pricing, plan by plan
Every plan each vendor publishes, monthly and yearly where both are offered.
Dust
Gumloop
Pros and cons
From each tool's full review, written from the same checked facts.
Dust
- Shared AI agents across departments ensure consistent outputs for all team members rather than siloed per-user chat threads.
- Multi-model backend supports GPT, Claude, Gemini, Mistral, and DeepSeek, giving teams flexibility in model selection.
- Semantic knowledge layer attempts to synthesize meaning across data sources rather than simple text retrieval.
- Agent builder allows scoped configuration with attached knowledge sources and tools deployed to specific teams.
- Collaborative Pods organize teams and agents together in a shared workspace with layered permissions.
- Enterprise-grade RBAC with dual-layer controls and SCIM-synced groups is more mature than most competing tools.
- Centralized knowledge base means a sales rep, support manager, and engineer can all get consistent results from the same agent.
- Limited presence on major review aggregators like G2 and Capterra makes independent verification of user experience difficult.
- Claims about the semantic knowledge layer's real-world performance are hard to verify without hands-on testing.
- The collaborative AI thesis works better for some teams than others, meaning it is not a universal fit.
- As a 2022 launch still outside mainstream review platforms, long-term reliability and support track record is unclear.
- The multiplayer workspace model may add complexity for smaller teams or individuals who just need simple AI chat.
- Enterprise features like SCIM-synced groups suggest the product skews toward larger organizations, potentially pricing out smaller teams.
Gumloop
- Canvas-based visual workflow builder makes it easy to design complex multi-step AI processes without writing code.
- Supports multiple AI models including OpenAI, Anthropic, Google Gemini, and DeepSeek, giving teams flexibility in model choice.
- Includes code sandboxes, which is rare for no-code tools and allows teams to extend functionality beyond standard nodes.
- Offers a range of trigger options including webhooks, scheduled runs, email, Slack, form submissions, and an API.
- Built-in conditional logic and a workflow queuing system with error handling and policy application.
- Backed by a $50M Series B led by Benchmark, signaling strong investor confidence and likely continued development.
- Positioned as an AI agent orchestrator rather than a simple task automator, targeting a more sophisticated automation use case.
- Total number of native integrations is not publicly disclosed, making it hard to evaluate compatibility before committing.
- MCP integrations are mentioned without any clear count or documentation transparency.
- The sophistication of the error handling system could not be independently verified from public information.
- This review is based entirely on research rather than hands-on testing, so real-world performance remains unconfirmed.
- As a two-year-old company, Gumloop is still early-stage and may carry product maturity and stability risks.
- The vague integration list around Salesforce, Slack, BigQuery, and Gmail lacks detail on depth or reliability of those connections.
Dust vs Gumloop: common questions
Which is better, Dust or Gumloop?
Gumloop scores 7.3 and Dust 5.7 out of 10 among the AI agent builders we rate. Gumloop is ahead on aI agents, building workflows, apps it connects to and hosting and security. Dust is ahead on pricing and reliability and control.
Is Dust or Gumloop cheaper?
Dust's cheapest paid plan is Free and Gumloop's is $37/mo — Pro. Compare what each plan includes below before going on price alone.
Do Dust and Gumloop have a free plan?
Dust does and Gumloop does not.
What can Dust do that Gumloop cannot?
On the facts both vendors publish: free plan.
What can Gumloop do that Dust cannot?
On the facts both vendors publish: visual builder.
