Agno vs Humanloop
Side-by-side comparison to help you choose the best tool.
Agno
freeAgno (formerly Phidata) is a lightweight open-source system for building multi-modal AI agents with memory, knowledge, and tools. It provides a simple Python API for creating agents that can search the web, query databases, and take actions, with built-in support for team workflows where multiple agents collaborate. Agno is known for its simplicity and performance versus more complex alternatives.
Humanloop
freemiumHumanloop is an LLM evaluation and prompt management platform that helps AI teams deploy, evaluate, and improve LLM applications in production. It provides prompt versioning, A/B testing, automatic evaluation with LLM judges, and user feedback collection. Used by companies like Canva, Accenture, and EDF to systematically improve their LLM product quality over time.
| Feature | Agno | Humanloop |
|---|---|---|
| Pricing | free | freemium |
| Category | - | - |
| Rating | 4.3 | 4.4 |
| Best For | Python developers building AI agents and multi-agent teams who want a simpler, lighter alternative to LangChain with excellent performance | Product teams deploying LLM applications who need systematic prompt evaluation, A/B testing, and quality monitoring in production |
| Views | 4 | 2 |
Pros
- Simpler and faster than LangChain for most agent use cases
- Built-in multi-agent team orchestration
- Active development with regular improvements
Cons
- Smaller ecosystem than LangChain or CrewAI
- Less documentation for complex use cases
Pros
- Systematic prompt improvement with version control
- LLM-as-judge evaluation at scale
- Used by enterprise product teams
Cons
- Requires LLM application to be instrumented
- Evaluation setup requires expertise
- Multi-modal AI agents
- Built-in memory & knowledge
- Agent team workflows
- Tool use & web search
- Simple Python API
- Prompt versioning & management
- LLM output evaluation
- A/B testing prompts
- User feedback collection
- Production monitoring