Izlo vs Langflow

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

	Izlo Agents	Langflow Agents
Tagline	Prompt management platform with version control, collaboration, and an API for production deployment.	Open-source visual builder for LangChain-style AI agents and RAG pipelines.
Category	Agents	Agents
Pricing	Paid· Solo $20/mo; Pro $25/user/mo; Enterprise $39/user/mo	Freemium· Open-source free; hosted free tier + paid enterprise via DataStax
Model	Model-agnostic	Multi-model
Editorial score	6.9 / 10	8.1 / 10
Use cases	prompt-managementversion-controlteam-collaborationprompt-testingproduction-deployment	agent-prototypingrag-pipelinesworkflow-automationllm-orchestrationchatbot-development
Pros	Git-style version history and activity log for every prompt change Remix sandbox isolates experiments from production prompts REST API lets you swap prompts without redeploying the app Built for multi-user team editing, not just solo developers	Open source and self-hostable with a permissive license Visual graph maps cleanly to LangChain concepts developers already know Broad LLM and vector-DB coverage out of the box Every node is editable Python, not a locked black box Flows deploy as APIs without extra glue code
Cons	No free tier; cheapest plan is $20/mo Stingy token allowance (5K/seat) for in-app testing Lighter on observability/analytics than Langfuse or Helicone Supported model providers not clearly listed on the site	Fast-moving codebase; version upgrades can break existing flows Visual metaphor still assumes LangChain-level familiarity Hosted tier is tied to DataStax's Astra ecosystem
Website	getizlo.com	www.langflow.org

Pick Izlo if

✅ Git-style version history and activity log for every prompt change
✅ Remix sandbox isolates experiments from production prompts
✅ REST API lets you swap prompts without redeploying the app
✅ Built for multi-user team editing, not just solo developers

Pick Langflow if

✅ Open source and self-hostable with a permissive license
✅ Visual graph maps cleanly to LangChain concepts developers already know
✅ Broad LLM and vector-DB coverage out of the box
✅ Every node is editable Python, not a locked black box

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