Agno is an agent platform designed to build, deploy, and manage AI agents in production environments. It supports agents built using any framework or no-code UI, providing production-grade features like tracing, scheduling, and RBAC. Agno allows teams to automate diverse tasks from data labeling and document extraction to product copilots while maintaining data ownership.

LlamaIndex provides a comprehensive framework for building LLM-powered applications, focusing on context augmentation to connect LLMs with private or specialized data. It supports developing everything from simple question-answering systems to complex agentic workflows with customizable components. Engineers can leverage its high-level APIs for quick starts or deep customization for production-grade applications.

• +Productionizes agents built with any framework, offering flexibility in agent creation.
• +Provides robust production features for agents, including tracing, scheduling, role-based access control (RBAC), and audit trails.
• +Supports management of the entire agent development lifecycle using coding agents.
• +Offers native typesafety and multi-modal capabilities for various input/output modalities, including structured output.
• +Ensures data ownership by storing all session, memory, and trace data in the user's own database and cloud.
• +Enables auto-improvement of agents using production usage data via provided code mechanisms.

• +Provides a leading framework for building LLM-powered agents and workflows over custom data.
• +Supports extensive context augmentation, enabling LLMs to interact with private or specific enterprise data.
• +Offers comprehensive tools for data ingestion, parsing, indexing, processing, and complex query workflows.
• +Features a high-level API for rapid prototyping, allowing users to start with as little as 5 lines of code.
• +Offers lower-level APIs for advanced users to customize and extend any module, including data connectors, indices, and engines.
• +Facilitates event-driven workflows that combine multiple agents and data sources, described as more flexible than graph-based approaches.
• +Includes observability and evaluation integrations to support rigorous experimentation and monitoring of LLM applications.
• +Provides managed services via LlamaCloud for enterprise-grade document parsing (LlamaParse), extraction, indexing, and retrieval.

• −no data

Agno stores all session, memory, and trace data in the user's own database within their cloud environment.

LlamaIndex manages state by orchestrating multi-step agentic workflows and conversational chat engines, allowing for reflection and error-correction in complex LLM applications.