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The Stack / Automation
Dynamiq
04 AutomationFor teams genuinely running multi-agent systems in production, Dynamiq's orchestration-plus-observability angle addresses the real problem: agents you can't see are agents you can't trust. Most operators aren't there yet — earn this seat after your first agents outgrow n8n.
The job in the stack
The agent-ops seat: building, orchestrating, and monitoring multi-agent AI systems with observability built in.
Pricing
| Plan | Price | Notes |
|---|---|---|
| Free | $0 | Dynamiq Cloud workspace, canvas or Python agent building, Apache-2.0 open-source SDK. Usage limits apply (apps, knowledge bases, app runs, ingestions); exact numbers are shown in-app, not on the pricing page |
| Enterprise | custom | Self-hosting, SSO, retention controls, SOC 2/HIPAA/GDPR support, forward-deployed engineers, SLA support. Priced by deployment, usage and engineering needs |
Pricing verified 2026-10-25. Plans change — the source of truth is Dynamiq's own pricing page.
Models & versions
- Agent orchestration Multi-agent workflows, RAG pipelines, tracing and evaluation
The honest read
What works
- + Observability and tracing — see what your agents actually did
- + Multi-agent orchestration with guardrails, not just chains
- + Self-hostable for data-boundary-sensitive teams
What breaks
- − Overkill until you're truly running agents in production
- − Smaller ecosystem and community than the big workflow tools
- − Technical seat — expects engineering comfort
Use it for
- →Teams productionizing multi-agent workflows with audit needs
- →RAG-heavy internal systems that need evaluation loops
- →Engineering-led operations building an agentic workforce deliberately
Skip it if
- ×You're automating tasks, not orchestrating agents — n8n first
- ×No engineer on the team — this seat assumes one
Questions operators ask
?When do I graduate from n8n to Dynamiq?
When your agents need supervision, not just scheduling — multiple agents coordinating, outputs that need evaluation, and 'what did it do and why' as a compliance question. Until then, n8n's agent nodes are the right-sized tool.
What changed
- Freshness sweep: getdynamiq.ai/pricing is live again and lists Free and custom Enterprise only. The Free tier no longer publishes the 1-workflow / 1,000-executions numbers ("usage limits apply", visible in-app), so we removed them. The Team tier is folded into Enterprise.
- Freshness sweep: no changes. Still no public pricing (sales call or free consultation for paid tiers); free start still offered on getdynamiq.ai. No new product announcements found since the last check.
- Freshness sweep: no changes. Pricing remains sales-gated with no public page; free dev tier (1 workflow, 1 RAG knowledge base, 1,000 executions/mo) still live at signup.
- Freshness sweep: no pricing change to verify — getdynamiq.ai's /pricing URL now returns 404 and the site offers only "Start for free" and a booked consultation. Free dev tier still live at signup.
- Freshness sweep: free dev tier confirmed with concrete limits (1 workflow, 1 RAG knowledge base, 1,000 executions/mo); paid tiers remain sales-gated with no public pricing. Prebuilt agents (medical research, legal assistant, OCR) now shipping.
- Freshness sweep: getdynamiq.ai has no public pricing page (paid tiers are sales-gated — "free consultation" only). Removed the seeded ~$49/mo estimate as unverifiable; free dev tier confirmed live.
- Added to the stack (agent-ops seat). Pricing seeded from January 2026 baseline, pending fresh verification by the update loop.
Give Dynamiq a job
The agent-ops seat: building, orchestrating, and monitoring multi-agent AI systems with observability built in.
Try Dynamiq →Affiliate link — same price for you, keeps the stack maintained.
Alternatives with different jobs
n8n
04 AutomationThe heavy-automation seat: complex, high-volume workflows and AI agent pipelines, self-hosted or cloud.
StackAI
04 AutomationThe internal-AI-apps seat: drag-and-drop LLM workflows — document processing, internal assistants, approval chains — deployed to your team.