Citation: This article is summarized from the original guide by Instaclustr.
Agentic AI frameworks are software toolkits that simplify the creation of autonomous AI agents, providing developers with pre-built components for tasks like perception, reasoning, action, and memory management to build complex, goal-driven systems. They act as blueprints for constructing intelligent agents capable of interacting with external systems and managing context over time.
Notable Agentic AI Frameworks
1. LangGraph
LangGraph is a framework from the LangChain ecosystem for building stateful, controllable agent workflows. It provides low-level primitives for designing single-agent and multi-agent systems with explicit control over execution flow, memory, and human-in-the-loop moderation.
2. AutoGen
AutoGen is a framework for building conversational AI agents and multi-agent systems with layered abstractions. It supports rapid prototyping through a web-based interface and programmatic development for scalable, event-driven agent orchestration.
3. CrewAI
CrewAI is a framework for building and operating coordinated teams of AI agents that execute complex workflows autonomously. It supports both visual development and API-driven integration, connecting agents to enterprise systems like Salesforce and Slack.
4. OpenAI Agents
OpenAI Agents provide a toolkit for building, deploying, and optimizing workflows using OpenAI models and platform components. Through AgentKit and Agent Builder, developers can seamlessly design workflows combining tools, memory, and control logic.
5. SuperAGI
SuperAGI is an AI-native platform that combines multiple AI-driven applications and agents into a unified system for business workflows. It focuses on embedding AI agents directly across functions such as sales, marketing, customer support, and operations.
6. LlamaIndex
LlamaIndex is a developer-focused framework for building document-centric AI agents and retrieval-augmented generation (RAG) systems. It provides modular components for parsing over 90 unstructured file types, memory orchestration, and retrieval.
7. Semantic Kernel
Semantic Kernel is a lightweight, open-source SDK for integrating AI models into C#, Python, and Java applications. It acts as middleware between language models and existing business logic, effectively translating model outputs into executable function calls.
8. AutoAgent
AutoAgent is an open-source, zero-code framework for building and deploying LLM agents using natural language. It allows users to create agents, tools, and automatically generate multi-agent workflows entirely through conversational inputs.
9. DSPy
DSPy (Declarative Self-improving Python) is a declarative framework for building modular AI systems using structured programming rather than manual prompt engineering. It compiles high-level definitions into optimized prompts and model weights.
10. Haystack
Haystack is an open-source AI orchestration framework for building production-ready agents and context-engineered applications. It provides modular pipelines that give developers maximum visibility into retrieval, reasoning, and tool usage.