The Lindy Alternative Built for Enterprise Scale
Lindy is a capable no-code builder for AI assistants and automations. Coworker is an enterprise AI platform: agents that act across 50+ connected tools with read and write access, organizational memory through OM1, and SOC 2 Type II security, at frontier quality for about 80% less. For lightweight personal automations, Lindy is handy; for company-wide agents with governance, Coworker fits.
Last updated: April 2026
3 tool requests
Meeting transcript
Extracted 4 action items from Acme call
Salesforce update
Stage → Discovery Complete, notes added
Follow-up draft
Recap email with POC timeline composed
Reasoning steps
What makes Coworker different
Organizational memory vs. per-flow context
Coworker
OM1 builds a persistent knowledge graph across your tools, so agents share company context rather than operating per-automation.
Lindy
Lindy automations run on the context configured per flow; there is no org-wide persistent memory model.
Side by side
Built to be enterprise-ready
Security, privacy, and compliance are not add-ons. They're foundational to every layer of the platform.
FAQ
Frequently asked questions
Coworker is a strong Lindy alternative for teams. Lindy is a no-code builder for AI assistants and automations. Coworker adds organizational memory through OM1, 50+ read and write connectors, enterprise security, and multi-model routing that cuts AI cost by about 80%.
Yes. You configure agents in plain English with triggers, scopes, data sources, and approval gates, no code required. The difference is that Coworker agents draw on org-wide memory and act across 50+ connected tools with inherited permissions.
Coworker starts at $29.99/user/month with a 14-day free trial and predictable per-seat pricing. Lindy is task-credit based, so costs scale with automation volume. Coworker's routing also reduces AI cost by about 80% versus frontier API rates.
Yes. Coworker is SOC 2 Type II certified, GDPR compliant, and CASA Tier 2 verified, with SSO, RBAC, encryption, audit trails, and approval gates. Your data is never used to train models.
Yes. Coworker agents can be scheduled, event-triggered, or invoked on demand, with approval gates for sensitive actions, running continuously across your connected tools.
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