Gumloop vs Sim
A detailed comparison to help you choose between Gumloop and Sim.
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Verdict: Sim wins
Sim scores 3.9/5, edging out Gumloop at 3.6/5. Technical teams that want an inspectable, self-hostable agent orchestration layer with real governance controls instead of a closed agent builder.
Gumloop Build AI agents with no-code workflows and API integrations | Sim Build and test AI agents without code | |
|---|---|---|
| Rating | 3.6 (1 review) | 3.9 (1 review) |
| Pricing Model | freemium | freemium |
| Starting Price | Free tier available | Free tier available |
| Best For | Teams that want non-engineers building AI-shaped automations — research, scraping, summarization — under centralized IT control and spend oversight. | Technical teams that want an inspectable, self-hostable agent orchestration layer with real governance controls instead of a closed agent builder. |
| Free Tier | ||
| API Access | ||
| Team Features | ||
| Open Source | ||
| Tags | no codefree tier | open sourcefree tierapi access |
| Visit Gumloop → | Visit Sim → |
Gumloop
Pros
- + Fastest AI-flow building I tested: scrape-summarize-extract agent went up in ~40 minutes, with a model swap as a drop-down change
- + IT control features are real on Pro (agent-scoped connector policies, shared credentials, usage analytics) and org-wide on Enterprise
- + Unlimited agents, seats, and teams on Pro from $37/mo — no per-seat tax, unlike most rivals (gumloop.com/pricing)
- + Hosted scraping node handled a JS-heavy site my plain HTTP attempt failed on
- + Well funded for its age: $17M Series A (Nexus) and a $50M Series B, with named customers like Shopify and Instacart
Cons
- - No free plan — 14-day trial only — and the 8% orchestration fee on top of credits makes heavy usage hard to predict
- - Credit costs vary by node and model; my scrape-heavy flow cost roughly triple the targeted version before I tuned it
- - Shallow for engineers: no code steps with real package access, no self-hosting (Enterprise VPC only), thin connector breadth versus Zapier/Make
- - Agent memory is flow-scoped — persistent cross-run context is early despite the self-improving-agent marketing
- - Pro concurrency caps (5 workflow runs, 25 agent chats) queued my bulk jobs; throughput is not the strong suit yet
Sim
Pros
- + Per-block run traces show inputs, outputs, duration and cost for every step — in my 50-run test this made the two retry-plagued runs immediately visible
- + Apache-2.0 codebase self-hosted via Docker Compose in about fifteen minutes in my test, with the same canvas and logs as the hosted workspace
- + Typed workflow vocabulary (Router, Guardrails, Evaluator, Human-in-the-Loop) forces you to say where decisions and quality checks happen
- + Free tier with 1,000 credits, plus per-member spend limits and permission groups for model and integration access
- + Deploys as chat, API or MCP server from the same workflow
Cons
- - Plan details churned through 2026: third-party trackers disagree on whether the free 1,000 credits are monthly or one-time
- - Integration count claims conflict — the homepage says 270+, directory listings say 1,000+
- - Governance stack (SSO, SOC 2, audit logs, self-hosting support) is gated at Enterprise pricing
- - Product launched publicly in 2025 and is still moving under users; no native mobile app
- - Support is a community repository below Enterprise
Frequently Asked Questions
Which is better, Gumloop or Sim?▼
Sim scores higher at 3.9/5 vs 3.6/5 for Gumloop, making it the better-rated option in our comparison.
What is the difference between Gumloop and Sim?▼
Gumloop: Gumloop is a no-code builder for AI agents and automations, where teams connect models and apps on a visual canvas. It is aimed at companies that want non-engineers to build automations under IT control. Sim: Sim is an open-source AI workspace where companies build, distribute and govern AI agents, with hundreds of integrations, all major LLMs and a self-hosting option.
Is Gumloop or Sim more affordable?▼
Gumloop starts at €0/mo, Sim starts at €0/mo. Check the comparison table above for current pricing.
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