Lindy vs Gumloop (2026): Pricing, Features & Winner

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AI Overview: Lindy vs Gumloop — Quick Verdict

Winner: Gumloop. Gumloop wins for building explicit AI-agent workflows; Lindy is better when teams want to delegate work conversationally in Slack, email and meetings. This comparison uses current official product and pricing information checked on 2026-09-16. There is no universal winner: the right platform depends on the workflow you are actually building, the team that will maintain it and the billing unit that drives your cost.

Category	Lindy	Gumloop
Best for	teams that want an AI teammate for Slack, email, meetings, scheduled routines and cross-app actions with approval controls	teams building AI-heavy agents and workflows that combine models, tools, browser actions and business data
Pricing model	per-user subscription plus pooled credits	credits tied to model/tool/compute usage
Free option	7-day trial for eligible new teammates joining through Slack; verify signup path	Trial/free access varies; verify live signup
Biggest strength	assistant-style automation across communication, meetings and connected business apps	AI-native workflow and agent building with broad model support
Main trade-off	per-user pricing can become expensive for broad deployment	usage-based AI economics require closer monitoring than simple task automation
Editorial winner	Gumloop — Gumloop wins for building explicit AI-agent workflows; Lindy is better when teams want to delegate work conversationally in Slack, email and meetings.

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The Core Difference

Lindy is strongest for teams that want an AI teammate for Slack, email, meetings, scheduled routines and cross-app actions with approval controls. Its defining strengths are assistant-style automation across communication, meetings and connected business apps and built-in approval behavior for actions with external impact. Gumloop, by contrast, is strongest for teams building AI-heavy agents and workflows that combine models, tools, browser actions and business data, with AI-native workflow and agent building with broad model support and flexible agent/tool composition, BYOK and enterprise controls.

That distinction is more useful than a generic feature checklist. Start by writing your trigger, expected monthly volume, apps involved, branching requirements, AI requirements, data sensitivity and the person who will maintain the workflow. Once those facts are clear, the choice usually narrows quickly.

Pricing Comparison

Lindy pricing

Plus is $29.99/user/month with 3,000 credits; Pro is $99.99/user/month with 15,000 credits; Max is $199.99/user/month with 35,000 credits; Enterprise is custom. Paid seats pool credits at the workspace level.

Gumloop pricing

Gumloop Pro starts around $37/month with 20,000 credits in current 2026 materials. Enterprise is custom. Gumloop’s newer model passes through token and compute costs and adds an orchestration fee; BYOK can reduce some AI-model credit usage.

The biggest mistake is comparing only monthly sticker prices. Lindy meters around per-user subscription plus pooled credits, while Gumloop meters around credits tied to model/tool/compute usage. Model the same workflow at 1×, 2× and 10× expected volume. Include paid seats, AI credits, premium connectors, hosting and the staff time required to operate the system.

Workflow Building Experience

Consider this workflow in Lindy: Slack request → read approved context → research → draft action → request approval → update CRM/email/doc → report completion. Now imagine the equivalent in Gumloop: inbox/web trigger → gather context → AI research/extract → call tools → human approval → update CRM/docs → report. Lindy feels strongest when built-in approval behavior for actions with external impact matters; Gumloop has the advantage when flexible agent/tool composition, BYOK and enterprise controls is more important.

A production workflow should be understandable by someone other than its creator. During your trial, ask a teammate to identify the trigger, inspect the input/output of a failed step, change a destination field and safely replay a run. The platform that makes these operations clearer may be the better long-term choice even if the initial build takes a few minutes longer.

Integrations and Extensibility

Lindy: Lindy is strongest when users want to delegate work conversationally rather than assemble every branch manually in a visual workflow builder.

Gumloop: Gumloop is strongest when model reasoning, research or unstructured data is central to the workflow rather than a single optional step.

Verify the exact connector, not just the logo. Check whether the integration supports the event you need, required fields, pagination, attachments, custom objects and API version. If either platform has an incomplete native connector, look for HTTP requests, webhooks, custom code, databases or MCP before ruling it out.

AI and Agentic Automation

Lindy: Lindy is positioned as an AI teammate with persistent context, scheduled routines, integrations, MCP, model selection and computer use.

Gumloop: Gumloop is designed around AI agents and workflow nodes, with model routing, BYOK, hosted MCP and policies on current Pro/Enterprise positioning.

For business-critical workflows, AI should not blur responsibility. Use models for classification, extraction, summarization and drafting, then validate structured output. Keep money movement, deletion, access changes and external publication behind deterministic rules or human approval. Compare how each platform lets you set those boundaries.

Reliability, Errors and Recovery

Lindy’s most important operational limitation is that credit consumption varies widely between small asks and deep multi-step work. Gumloop’s corresponding limitation is that teams focused on deterministic app-to-app workflows may prefer a simpler classic automation platform. During testing, deliberately break the workflow: send a blank field, revoke a connection, cause a duplicate event and force an API error. Measure how quickly you can locate the failure, understand the payload and retry without duplicating downstream actions.

Team Governance and Security

Lindy: Enterprise adds SSO, audit logs, HIPAA/BAA options and dedicated support; the product emphasizes approvals before external actions.

Gumloop: Enterprise materials reference SSO/SCIM, RBAC, audit logs, model controls, data-retention controls and optional VPC support.

Governance can be ignored in a personal prototype and become the deciding factor at 50 users. Compare roles, shared credentials, SSO, audit logs, environments, secrets management, version history and data retention at the exact plan you intend to buy.

When Lindy Is the Better Choice

You specifically need assistant-style automation across communication, meetings and connected business apps.
Built-in approval behavior for actions with external impact matters more than flexible agent/tool composition, BYOK and enterprise controls.
Your team matches this profile: teams that want an AI teammate for Slack, email, meetings, scheduled routines and cross-app actions with approval controls.
You can accept that per-user pricing can become expensive for broad deployment.
Its pricing unit (per-user subscription plus pooled credits) fits your expected usage better.

When Gumloop Is the Better Choice

You specifically need AI-native workflow and agent building with broad model support.
Flexible agent/tool composition, byok and enterprise controls is more important.
Your team matches this profile: teams building AI-heavy agents and workflows that combine models, tools, browser actions and business data.
You can accept that usage-based AI economics require closer monitoring than simple task automation.
Its pricing unit (credits tied to model/tool/compute usage) fits your workload better.

Four Decision Scenarios

Small agency or SMB

For a small agency, prioritize speed, maintainability and predictable cost. Gumloop is our default winner in this matchup, but only after confirming the exact CRM, form, email and reporting connectors you need.

Technical AI automation team

If APIs, custom logic, model calls and databases dominate, give extra weight to extensibility and observability. Lindy benefits from assistant-style automation across communication, meetings and connected business apps; Gumloop benefits from AI-native workflow and agent building with broad model support.

Enterprise or regulated team

Ignore entry pricing for a moment. Compare SSO, roles, auditability, environments, secret storage, support SLAs and data-handling commitments. The enterprise winner can be different from the SMB winner.

High-volume workflow

At high volume, rebuild the economics from first principles. Count records, executions, tasks, credits, users and AI calls. Include support and engineering time. The lowest starter price is rarely the most useful metric.

Migration Checklist

Export or document the existing workflow before making changes.
List every trigger, filter, mapping, credential, schedule and error branch.
Create stable source IDs so parallel testing cannot create duplicates.
Rebuild one representative workflow first rather than migrating everything.
Run old and new systems in parallel where safe.
Compare usage units, errors and completion results for at least one full business cycle.
Switch production traffic only when rollback and ownership are clear.

Final Verdict

Gumloop wins this comparison. Gumloop wins for building explicit AI-agent workflows; Lindy is better when teams want to delegate work conversationally in Slack, email and meetings. If your requirements are close, run the same workflow with the same sample data in both products for two weeks. Record build time, monthly usage units, failure-recovery time and the time a second person needs to understand the automation.

Lindy vs Gumloop: FAQs

Which is easier to use, Lindy or Gumloop?

Lindy emphasizes built-in approval behavior for actions with external impact; Gumloop emphasizes flexible agent/tool composition, BYOK and enterprise controls. Ease depends on whether your team prefers the first or second operating style.

Which is cheaper, Lindy or Gumloop?

There is no universal answer because Lindy meters around per-user subscription plus pooled credits while Gumloop meters around credits tied to model/tool/compute usage. Model your real volume instead of comparing entry prices.

Which is better for AI automation?

Lindy: Lindy is positioned as an AI teammate with persistent context, scheduled routines, integrations, MCP, model selection and computer use. Gumloop: Gumloop is designed around AI agents and workflow nodes, with model routing, BYOK, hosted MCP and policies on current Pro/Enterprise positioning. The better option depends on whether AI is one controlled step or the central agentic layer.

Can I migrate between them?

Yes, but not usually with one-click portability. Treat the migration as a process redesign and test every credential, field mapping and failure path.

What should I test before buying?

Use one representative workflow with at least one branch, one invalid-data case, a real downstream system and a clear error-recovery step. Compare maintainability as well as setup speed.

Lindy vs Gumloop 2026: Pricing, Features & Winner