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Agno
Open Source
Best for developers
Self-hosted AI agents
Multi-agent orchestration
High performance framework
Data privacy focused
A new architecture for multi-agent systems that runs in your cloud.
Last updated: Apr 25, 2026
FREEMIUM
agno.com
Quick Answer
Agno is an open-source multi-agent framework and runtime that enables developers to build, deploy, and manage secure, high-performance AI agent systems directly within their own cloud. It supports self-learning agents, multi-agent orchestration, and extensive tool use with any LLM. Best for developers and platform teams prioritizing privacy, performance, and control over their AI infrastructure. Offers a free open-source tier and paid plans for production.
About Agno
Agno is an all-in-one agent platform providing an open-source Python framework and a high-performance runtime for multi-agent systems. It enables developers to build, run, and manage self-learning agents with memory, knowledge, and guardrails in their own cloud environment. Agno offers a secure, private, and scalable solution for deploying production-ready AI agent infrastructure.
What Makes It Unique
Agno stands out with its 'pure Python' design, eliminating complex graphs or chains, and its AgentOS runtime that turns agents into a scalable API running entirely in the user's cloud. It boasts significantly faster agent instantiation and lower memory footprint compared to alternatives like LangGraph and CrewAI.
Use Cases & Target Users
Best For
Building and deploying multi-agent systems for developers
Orchestrating complex AI workflows in production environments
Ensuring data privacy and security for agentic applications
Teams needing high-performance and low-latency agent execution
Integrating AI agents with existing cloud infrastructure
Company Size
SOLO
SMALL
MEDIUM
ENTERPRISE
Fit Score
Complexity
ADVANCED
Target Team Size
SMALL_TEAM
LARGE_TEAM
Target Skill Level
EXPERT
Key Features
Open-source Python agent framework
High-performance AgentOS runtime for multi-agent systems
Built-in control plane for chat, tracing, and monitoring
Secure and private architecture with JWT, RBAC, and request-level isolation
Support for self-learning agents with persistent memory and knowledge
Cron-based scheduling for agents, teams, and workflows
Technical Specifications
API Available
SDK Available
MCP Compatible
Open Source
Apache-2.0
Team Features
SSO/Enterprise
Webhook Support
Has Demo
Deployment:
HYBRID
Pros
- +Runs entirely in your cloud, ensuring data privacy and control with no egress costs
- +Significantly faster agent instantiation and lower memory footprint than competitors
- +Flexible and agnostic, supporting any LLM, database, and cloud provider
- +Comprehensive control plane for real-time monitoring, tracing, and management
- +Robust human-in-the-loop capabilities for controlled agent execution
- +Open-source framework with a strong community and extensive documentation
Limitations
- -Requires Python knowledge and coding skills, not suitable for no-code users
- -Self-hosted deployment requires user's own cloud infrastructure management
- -Newer framework compared to established alternatives like LangChain, potentially smaller ecosystem
- -Advanced features like custom SSO and dedicated support are locked behind enterprise tiers
Uses Models
Claude Sonnet 4.6GPT-4oNeosantaraMoonshot
Decision Intelligence
Best For
Building and deploying multi-agent systems for developers
Orchestrating complex AI workflows in production environments
Ensuring data privacy and security for agentic applications
Teams needing high-performance and low-latency agent execution
Integrating AI agents with existing cloud infrastructure
Not Ideal For
Non-technical users seeking a no-code agent builder
Teams unwilling to manage their own cloud infrastructure
Simple, single-step automation tasks that don't require agentic capabilities
Users looking for a fully managed, hosted AI agent solution without self-hosting
Frequently Asked Questions
Your Actions
Dimension Scores
Ease of Use6/10
Output Quality8/10
Value for Money7/10
Customization9/10
Support7/10
Integration8/10
Task Scores
Api Connectivity
9
Monitoring Logging
9
Multi Step Chains
9
Workflow Building
8
Scheduling Capability
8
Conditional Logic
8
Autonomous Execution
8
Action Library
7
Trust Score
37/100
Limited Data
Based on 6 data signals
Reflects publicly available data, not an independent audit
Company Strength25/25
Team Size11-50
Funding$5.4M
Company ListedAgno Inc.
Operational Trust12/20
Switching & Migration
Migration Difficulty
Moderate Effort
Data portable as:
API
Community Forum, Dedicated Slack, Dedicated Technical Lead, Support SLA
PyPI31.0K/mo
Quick Stats
CategoryWorkflow Orchestration
PlatformsWEB, API, CLI
Integrations23+
Views5
LaunchedJan 2025
Setup Time2 minutes
AddedFeb 2026
Company & Links