Top 7 platforms & frameworks for building AI agents in 2025

AI agents are becoming the next big thing in tech. Y Combinator recently highlighted how vertical AI agents - specialized AI tools focusing on specific business tasks - could become 10 times bigger than traditional SaaS companies. Why? Because these AI agents can automate complex business tasks more efficiently than ever before.

The numbers speak for themselves. According to MarketsAndMarkets, the AI agents market is worth $5.1 billion in 2024 and is expected to reach $47.1 billion by 2030. The best part? You no longer need to be an AI expert to build an AI agent. Thanks to new platforms and frameworks, anyone can create their own AI agent, even without coding experience.

In this blog, we'll explore the top 7 platforms and frameworks that are making AI agent development accessible to everyone:

• Lyzr AI: A low-code agent framework for building Private & Secure GenAI applications faster.
• Autogen: Microsoft's solution for creating multiple AI agents that can work together to solve complex problems.
• Dify: A user-friendly platform with visual tools for building AI applications, perfect for both developers and non-technical users.
• LangGraph: A LangChain extension that helps create stateful, multi-agent systems with advanced planning capabilities.
• Swarm: OpenAI's experimental framework for simple and lightweight multi-agent orchestration.
• LlamaIndex: A data framework that helps connect large language models with various data sources efficiently.
• LangChain: A popular framework for building complex AI applications by connecting different language models and tools.

Let's dive deeper into each platform and see which one is right for your needs.

What are AI agents?

AI agents are software programs designed to perform tasks on their own, without needing constant human supervision. They observe their environment, process information, make decisions, and take action to achieve specific goals. In simple terms, an AI agent works like a smart assistant that can handle tasks intelligently and efficiently.

Think of an AI agent as a smart digital assistant that can:

• Understand its surroundings through data collection
• Make decisions based on the information it gathers
• Take actions to accomplish assigned goals
• Learn and improve from its experiences

What makes AI agents special is their ability to be rational and autonomous. They can process information, make informed decisions, and take actions without constant human supervision. This makes them powerful tools for automating tasks, handling large amounts of data, and scaling operations efficiently.

1. Lyzr AI:

Lyzr is a low-code agent framework with an agentic approach to building generative AI applications. Its fully integrated agents come with pre-built RAG (Retrieval-Augmented Generation) pipelines, allowing you to build and launch AI-powered solutions within minutes. With Lyzr, you can create chatbots, knowledge search engines, data analysis tools, RAG-powered apps, and multi-agent workflow automations—all with minimal effort.

Key Features:

• Locally Deployable SDKs: Install and run Lyzr on your own cloud infrastructure to maintain complete data control.
• Private APIs: Keep your generative AI applications behind your company's firewall, ensuring strong data governance.
• AI Management System (AIMS): A central control hub to manage agents, monitor logs, build with AI studios, and track AI usage.
• Lyzr Automata: A multi-agent automation framework that focuses on workflow efficiency. Create multiple agents each with specific tasks and goals, running them independently or in parallel.
• Pre-Built RAG Pipelines: Easily implement retrieval-augmented generation for more contextually accurate AI responses.
• Minimal Learning Curve: A low-code approach makes it accessible to developers and enterprise teams alike.

Best For:

• Developers seeking a simple yet powerful framework to quickly build AI apps
• CTOs and CPOs wanting to integrate generative AI features into existing applications without exposing data externally
• CIOs requiring 100% data privacy and security, with the ability to locally host AI solutions
• Enterprises looking for easy management of multiple agents and comprehensive AI analytics

Not Suitable For:

• Hobbyists or very small projects that do not need enterprise-level data privacy or compliance
• Teams unwilling to manage their own infrastructure or cloud resources