Izlo vs MemOS

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

	Izlo Agents	MemOS Agents
Tagline	Prompt management platform with version control, collaboration, and an API for production deployment.	Memory operating system that gives LLM agents long-term, structured recall across sessions and models.
Category	Agents	Agents
Pricing	Paid· Solo $20/mo; Pro $25/user/mo; Enterprise $39/user/mo	Freemium· Free tier; Starter $19/mo, Pro $286/mo (promo $0 at launch); Enterprise custom
Model	Model-agnostic	Multi-model
Editorial score	6.9 / 10	6.9 / 10
Use cases	prompt-managementversion-controlteam-collaborationprompt-testingproduction-deployment	agent-memorylong-term-contextrag-infrastructurepersonalizationknowledge-graph
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 core with a hosted managed option Structured memory plus dynamic knowledge graph, not just vector recall Cross-model memory sharing and MCP integration Self-host, on-prem, and hybrid deployment supported
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	Infrastructure piece, requires engineering work to integrate Younger ecosystem than vector DBs like Pinecone or Weaviate Pricing for paid tiers is steep once promo ends
Website	getizlo.com	memos.openmem.net

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 MemOS if

✅ Open-source core with a hosted managed option
✅ Structured memory plus dynamic knowledge graph, not just vector recall
✅ Cross-model memory sharing and MCP integration
✅ Self-host, on-prem, and hybrid deployment supported

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