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Agno vs Lindy.ai

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 source40k stars
Agno

High-performance multi-agent framework — build, run and manage teams of AI agents at scale

Closed sourceN/A stars
Lindy.ai

Enterprise productivity assistant with 4,000+ integrations

Category
Agno
Lindy.ai
Tagline
High-performance multi-agent framework — build, run and manage teams of AI agents at scale
Enterprise productivity assistant with 4,000+ integrations
Deployment
Self-hosted / Agno Cloud
Managed SaaS
Pricing
Open source and free to self-host. Agno Cloud available for managed deployments.
Mid-tier paid pricing that fits regular professional use better than hobby use.
Channels
Web, api, CLI
iMessage, SMS, Email, Web
Open source
Yes
No
Privacy
Self-hosted deployments keep data on your infrastructure.
Some privacy controls exist, but vendor-hosted infrastructure still handles a meaningful share of the data flow.
Agno pros
  • Extremely fast — benchmarks show 3x LangGraph speed.
  • Native multi-agent team support built-in.
  • Strong memory architecture with multiple storage backends.
Lindy.ai pros
  • Security posture is strong for sensitive workflows.
  • Extensible enough for custom tools, plugins, or workflow glue.
  • Good memory and persistence support for ongoing conversations or tasks.
Agno cons
  • Developer-focused — no visual builder.
  • Ecosystem smaller than LangChain/LangGraph.
  • Requires Python knowledge.
Lindy.ai cons
  • No modern chat apps (no Telegram, WhatsApp, Discord, Slack)
  • Lower privacy score — data processed on their servers
  • Closed source with mid-tier pricing
Agno gotchas
  • Formerly called Phidata — old docs may use old name.
  • Start with single agent before multi-agent orchestration.
Lindy.ai gotchas
  • Recurring subscription or model spend can matter more than the headline feature list.

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