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AI AGENTS

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Top 10 AI Agent Builders and Frameworks for Everyone

Updated: 2 days ago

The new AI gold rush is on, but instead of ready-made tools, today's prospectors need smarter tools to build intelligent and autonomous agents. Autonomous AI agents are no longer hype; they are now in action, ready to be made and deployed. Nearly half of technology leaders now say AI frameworks are fully baked into core business strategy, up from 28% a year ago, according to PwC's October 2024 Pulse Survey and according to Lyzr's State of AI Agents H1 2025 report, 64% of enterprise AI agent deployments are now focused on automating core business processes.


What are AI Agents?


AI agents are intelligent and powerful software capable of performing tasks autonomously without constant supervision.


How to build an AI agent?


Most people might think building an autonomous system is hard, and it might be true to some extent; however, it is not as hard as you might think, thanks to AI agent builders and frameworks that are readily available.


Anyone can bring their AI visions, i.e., those brilliant autonomous agents, tireless automation, and insightful analysts, to life faster than you thought was possible. Yes, that's exactly where AI agent builders and frameworks come in.


These AI agent platforms and frameworks aren't just another set of developer utilities; they're your fast way from 'imagine if' to 'look what I built.' We'll show you the top 10 AI agent builders and frameworks for everyone that make building capable AI agents a practical reality for more people than ever.


Here are the top 10 AI agent builders and frameworks for everyone:


No-code AI Agent Builders:



BuildThatIdea is designed for speed and simplicity, allowing creators to get AI applications up and running very quickly, with a focus on monetization. It's a good fit for those who want to test ideas or launch straightforward AI tools without getting bogged down in code. You can describe your app's function, pick a base language model (OpenAI, Claude, DeepSeek, Tulu, others), and set it live.


  • Get your AI application going in about a minute.

  • Define your app's purpose and behavior through descriptions and custom instructions; no code is needed.

  • Supports various large language models like those from OpenAI, Claude, and DeepSeek.

  • Launch for free or set up paid access with monthly subscriptions based on usage.

  • Useful for validating AI app ideas and iterating quickly.



Browser Use is an AI agent specifically designed to automate repetitive tasks performed in a web browser. It is an AI browser automation to manage web interactions that pairs advanced vision AI models with HTML extraction, letting agents click, scrape, or fill forms. Browser Use can handle multi-tab sessions, XPath element tracking, and self-healing errors.


  • Focuses on automating repetitive online activities.

  • Accessible to users without programming skills.

  • Combines visual understanding with HTML structure analysis for web interaction.

  • Can handle multiple browser tabs for complex workflows.

  • Features intelligent error handling and automatic recovery for more dependable automation.

  • Works with LangChain-compatible LLMs like GPT-4, Claude 3, and Llama 2.


Low-code AI Agent Builders and Frameworks:


3. n8n


n8n is a visual workflow builder that helps you connect AI agents with a large ecosystem of other applications and services, making it strong for building integrated AI-powered workflows. It offers flexibility for both technical users who prefer coding and those who favor visual development, allowing anyone to build automated sequences involving multiple steps and data sources.


  • Connects with over 422 apps and services.

  • Easily bring data from files, websites, or databases into your AI applications.

  • It offers both a drag-and-drop interface and code-based construction.

  • Host on your own premises for more control, or use their cloud service.

  • Engage with users via Slack, Teams, SMS, voice, or an embedded chat interface.



Voiceflow concentrates on building sophisticated AI agents for customer interactions, covering both chat and voice channels 24/7 while handing off tricky cases to humans. It's designed for product teams who need a dedicated platform to develop, manage, and observe conversational AI agents that focus on human-like interactions.


  • Specializes in building agents for chat and voice-based customer support.

  • Allows different teams within an organization to build AI agents securely.

  • Provides tools for managing agent performance and behavior.

  • Allows for deep capabilities and interface adjustments for chat agents.

  • Product teams can use their preferred large language models (LLMs) along with customer data.



CrewAI is a platform for creating and deploying multi-agent systems designed to automate workflows across different industries. It supports both coding and no-code approaches, offering a framework, UI Studio, and monitoring console for building, testing, deploying, and monitoring these AI "crews" as they perform tasks.


  • Build workflows using teams of AI agents.

  • Use the CrewAI framework for coding or the UI Studio for no-code development and templates.

  • Provides tools for moving agent crews to production and tracking their performance.

  • Allows for human oversight and feedback in agent operations.

  • Track your AI agents' quality, efficiency, and return on investment.



Scout provides a toolkit for building AI systems, focusing on creating AI workflows and preparing data for AI use. It allows users to combine AI models, web scraping, data storage, and API calls to build custom AI applications and solutions, all from a CLI or web studio.


  • Build automation using AI models, web scraping, data storage, and APIs.

  • Set up systems to automatically pull in content from websites, documents, and past conversations.

  • Connect several large language models (LLMs) within a single workflow.

  • Build unique AI applications using Scout's SDKs and APIs.

  • Offers evaluation tools and real-time monitoring to maintain result quality, along with logging for iteration.


Code-related AI Agent Builders and Frameworks:



Eliza is a framework focused on building and managing multiple autonomous AI agents that can work together. It is an open-source TypeScript stack geared towards developers looking to build intelligent agents that can operate across different platforms while maintaining consistent personalities and knowledge bases. It bundles retrievable memory, document ingestion, and pluggable "actions" you can script yourself.


  • Design systems where multiple AI agents interact.

  • Includes ready-to-use connectors for Discord, X (Twitter), and Telegram.

  • Works with different language models, including Llama, Grok, OpenAI, Anthropic, and Gemini.

  • Allows agents to access and use information from your documents easily.

  • Developers can create custom actions and clients to expand their capabilities.



LlamaIndex is centered on building retrieval-augmented agents or, in simple words, AI knowledge assistants that can operate over complex enterprise data. It provides tools to create production-ready agents capable of finding information, generating insights, creating reports, and taking action based on your company's data.


  • It specializes in agents who work with internal business data.

  • Offers a complete set of tools to take a context-aware AI agent to production.

  • LlamaCloud is a service that connects unstructured data to LLM agents securely.

  • Provides a leading developer framework for building context-augmented agents.

  • Convert agents into full-stack applications with features like multi-modal retrieval.



LangGraph is a framework that adds a layer of control and state management to complex AI agent workflows. It tries to strike a balance between letting agents operate autonomously and providing developers with the means to guide and moderate their actions, particularly for complex tasks. Developers can pause, rewind, or insert human approval checkpoints while keeping token-by-token streaming for UX.


  • Manages the state of agent workflows for more complex operations.

  • Design agents that can handle intricate tasks reliably with added moderation.

  • Easily add points for human review and approval of agent actions.

  • Low-level components allow for building diverse control flows (single-agent, multi-agent, hierarchical).

  • Built-in memory stores conversation histories for richer, personalized interactions over time.

  • Shows agent reasoning and actions, token-by-token, for a better user experience.



Smolagents by Hugging Face is a lightweight library that allows developers to run AI agents that think in code with minimal code. Its main appeal is simplicity, offering a straightforward way to implement agents, particularly "Code Agents" that write their own actions as code snippets inside a Docker or E2B sandbox.


  • The main logic for agents is contained in a relatively small amount of code.

  • Keeps the complexity low, staying close to raw code.

  • Specializes in agents that generate and execute code to perform actions.

  • Supports running code in secure environments through E2B or Docker for safety.


Conclusion


AI agent builders and frameworks now span the spectrum—from no-code point-and-click agent launchers like BuildThatIdea to intricate code-first frameworks for developers needing fine-grained control and integration like smolagents. Your choice depends on control, data gravity, and deployment comfort: marketers can ship a monetized chatbot in an hour, while platform engineers might embed LangGraph or LlamaIndex deep inside their stack. What's clear is that an "agent factory" mindset is spreading fast; picking the right AI agent builder and framework today is important for everything your organization automates tomorrow.

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