Flowise vs Letta
Side-by-side comparison of two agent options that often come up together when people are choosing between self-hosted frameworks, managed assistants, and extensible AI tooling.
Open source52k stars
Flowise
Visual drag-and-drop builder for AI agents and LLM workflows — no code required
Open source22k stars
Letta
Platform for building stateful agents with advanced memory persistence
Category
Flowise
Letta
Tagline
Visual drag-and-drop builder for AI agents and LLM workflows — no code required
Platform for building stateful agents with advanced memory persistence
Deployment
Self-hosted / Flowise Cloud
Self-Hosted
Pricing
Open source and free to self-host. Flowise Cloud starts at $35/month.
Usually affordable for individuals or small teams, with some recurring model or hosting costs.
Channels
Web, api, Slack, Teams
Telegram, Slack, Discord, WhatsApp, Signal
Open source
Yes
Yes
Privacy
Self-hosted deployment keeps data on your infrastructure.
Good privacy posture for most teams, especially when self-hosted or carefully configured.
Flowise pros
- Visual builder — no code required.
- Largest ecosystem of integrations of any open-source agent builder.
- 51K+ GitHub stars, active community.
Letta pros
- Open source with transparent code and flexible deployment options.
- Strong privacy story for users who care where data runs.
- Good memory and persistence support for ongoing conversations or tasks.
Flowise cons
- Visual workflows hard to debug at scale.
- Less flexible than code-first frameworks.
- Self-hosting requires some DevOps knowledge.
Letta cons
- Lower autonomy — designed more as a platform than an out-of-box assistant
- Setup requires understanding memory architecture concepts
- Python-only — no native TypeScript/JavaScript implementation
Flowise gotchas
- Complex flows can hit LLM rate limits silently.
- Docker deployment recommended over npm for stability.
Letta gotchas
- You should expect ongoing hosting, uptime, and secret-management work if you deploy it for real users.
- Recurring subscription or model spend can matter more than the headline feature list.
Not sure which one fits you?
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