Best AI Agent Builders for Agent Control
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Compare the Top AI Agent Builders that integrate with Agent Control as of June 2026
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This a list of AI Agent Builders that integrate with Agent Control. Use the filters on the left to add additional filters for products that have integrations with Agent Control. View the products that work with Agent Control in the table below.
What are AI Agent Builders for Agent Control?
AI agent builders are tools, platforms, or frameworks designed to create, train, and deploy intelligent virtual agents capable of performing tasks autonomously. These builders provide resources for natural language processing, decision-making algorithms, and machine learning, enabling agents to interact with users effectively. They often include user-friendly interfaces or APIs to customize behaviors, integrate with existing systems, and adapt to specific use cases. AI agent builders are widely used across industries, including customer service, healthcare, education, and entertainment, to enhance efficiency and user experience. By leveraging these tools, developers and businesses can rapidly create sophisticated agents tailored to their unique needs. Compare and read user reviews of the best AI Agent Builders for Agent Control currently available using the table below. This list is updated regularly.
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1
LangGraph
LangChain
Gain precision and control with LangGraph to build agents that reliably handle complex tasks. Build and scale agentic applications with LangGraph Platform. LangGraph's flexible framework supports diverse control flows – single agent, multi-agent, hierarchical, sequential – and robustly handles realistic, complex scenarios. Ensure reliability with easy-to-add moderation and quality loops that prevent agents from veering off course. Use LangGraph Platform to templatize your cognitive architecture so that tools, prompts, and models are easily configurable with LangGraph Platform Assistants. With built-in statefulness, LangGraph agents seamlessly collaborate with humans by writing drafts for review and awaiting approval before acting. Easily inspect the agent’s actions and "time-travel" to roll back and take a different action to correct course.Starting Price: Free -
2
AutoGen
Microsoft
An Open-Source Programming Framework for Agentic AI. AutoGen provides multi-agent conversation framework as a high-level abstraction. With this framework, one can conveniently build LLM workflows. AutoGen offers a collection of working systems spanning a wide range of applications from various domains and complexities. AutoGen supports enhanced LLM inference APIs, which can be used to improve inference performance and reduce cost.Starting Price: Free -
3
Agent Development Kit (ADK)
Google
The Agent Development Kit (ADK) is a flexible, open-source framework for building and deploying AI agents. It is tightly integrated with Google’s ecosystem, including Gemini models, and supports popular large language models (LLMs). ADK simplifies the development of both simple and complex AI agents, providing a structured environment for building dynamic workflows and multi-agent systems. With built-in tools for orchestration, deployment, and evaluation, ADK helps developers create scalable, modular AI solutions that can be easily deployed on platforms like Gemini Enterprise Agent Platform or Cloud Run.Starting Price: Free -
4
OpenAI Agents SDK
OpenAI
The OpenAI Agents SDK enables you to build agentic AI apps in a lightweight, easy-to-use package with very few abstractions. It's a production-ready upgrade of our previous experimentation for agents, Swarm. The Agents SDK has a very small set of primitives, agents, which are LLMs equipped with instructions and tools; handoffs, which allow agents to delegate to other agents for specific tasks; and guardrails, which enable the inputs to agents to be validated. In combination with Python, these primitives are powerful enough to express complex relationships between tools and agents, and allow you to build real-world applications without a steep learning curve. In addition, the SDK comes with built-in tracing that lets you visualize and debug your agentic flows, evaluate them, and even fine-tune models for your application.Starting Price: Free -
5
Strands Agents
Strands Agents
Strands Agents is an open-source framework designed to help developers build controllable and flexible AI agents using Python and TypeScript. It enables users to create agents by defining tools as simple functions, eliminating the need for complex workflows or orchestration pipelines. The SDK works with any model and cloud provider, giving developers full freedom in how they deploy and scale their agents. It introduces a streamlined agent loop where the model handles reasoning while developers maintain control through code. Features like steering hooks allow developers to validate and guide agent behavior before and after actions are taken. The platform also includes built-in capabilities such as memory management, observability, and evaluation tools. Overall, Strands Agents SDK simplifies agent development while improving reliability, control, and performance.Starting Price: Free -
6
Amazon Bedrock
Amazon
Amazon Bedrock is a fully managed service that simplifies building and scaling generative AI applications by providing access to a variety of high-performing foundation models (FMs) from leading AI companies such as AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon itself. Through a single API, developers can experiment with these models, customize them using techniques like fine-tuning and Retrieval Augmented Generation (RAG), and create agents that interact with enterprise systems and data sources. As a serverless platform, Amazon Bedrock eliminates the need for infrastructure management, allowing seamless integration of generative AI capabilities into applications with a focus on security, privacy, and responsible AI practices. -
7
CrewAI
CrewAI
CrewAI is a leading multi-agent platform that enables organizations to streamline workflows across various industries by building and deploying automated processes using any Large Language Model (LLM) and cloud platform. It offers a comprehensive suite of tools, including a framework and UI Studio, to facilitate the rapid development of multi-agent automations, catering to both coding professionals and those seeking no-code solutions. The platform supports flexible deployment options, allowing users to move their created 'crews'—teams of AI agents—to production with confidence, utilizing powerful tools for different deployment types and autogenerated user interfaces. CrewAI also provides robust monitoring capabilities, enabling users to track the performance and progress of their AI agents on both simple and complex tasks. Additionally, it offers testing and training tools to continually enhance the efficiency and quality of outcomes produced by these AI agents.
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