Alternatives to Agno
Compare Agno alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Agno in 2026. Compare features, ratings, user reviews, pricing, and more from Agno competitors and alternatives in order to make an informed decision for your business.
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1
Vertex AI
Google
Build, deploy, and scale machine learning (ML) models faster, with fully managed ML tools for any use case. Through Vertex AI Workbench, Vertex AI is natively integrated with BigQuery, Dataproc, and Spark. You can use BigQuery ML to create and execute machine learning models in BigQuery using standard SQL queries on existing business intelligence tools and spreadsheets, or you can export datasets from BigQuery directly into Vertex AI Workbench and run your models from there. Use Vertex Data Labeling to generate highly accurate labels for your data collection. Vertex AI Agent Builder enables developers to create and deploy enterprise-grade generative AI applications. It offers both no-code and code-first approaches, allowing users to build AI agents using natural language instructions or by leveraging frameworks like LangChain and LlamaIndex. -
2
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 -
3
LangChain
LangChain
LangChain is a powerful, composable framework designed for building, running, and managing applications powered by large language models (LLMs). It offers an array of tools for creating context-aware, reasoning applications, allowing businesses to leverage their own data and APIs to enhance functionality. LangChain’s suite includes LangGraph for orchestrating agent-driven workflows, and LangSmith for agent observability and performance management. Whether you're building prototypes or scaling full applications, LangChain offers the flexibility and tools needed to optimize the LLM lifecycle, with seamless integrations and fault-tolerant scalability. -
4
FastAgency
FastAgency
FastAgency is an open source framework designed to accelerate the deployment of multi-agent AI workflows from prototype to production. It provides a unified programming interface compatible with various agentic AI frameworks, enabling developers to deploy agentic workflows in both development and production settings. With features like multi-runtime support, seamless external API integration, and a command-line interface for orchestration, FastAgency simplifies the creation of scalable, production-ready architectures for serving AI workflows. Currently, it supports the AutoGen framework, with plans to extend support to CrewAI, Swarm, and LangGraph in the future. Developers can easily switch between frameworks, choosing the best one for their project's specific needs. FastAgency also features a common programming interface that enables the development of core workflows once and reuse them across various user interfaces without rewriting code.Starting Price: Free -
5
Crewship
Crewship
Crewship is the developer-first platform for deploying AI agent workflows. Deploy your CrewAI, LangGraph, and LangGraph.js agents with a single command and watch them execute in real-time. Key features include one-command deployment, real-time execution streaming, artifact management, auto-scaling, version control, and encrypted secrets management. Crewship handles infrastructure so developers can focus on building great AI agents. Multi-framework support with AutoGen, Pydantic AI, smolagents, OpenAI Agents, Mastra, and Agno coming soon.Starting Price: Free -
6
LangMem
LangChain
LangMem is a lightweight, flexible Python SDK from LangChain that equips AI agents with long-term memory capabilities, enabling them to extract, store, update, and retrieve meaningful information from past interactions to become smarter and more personalized over time. It supports three memory types and offers both hot-path tools for real-time memory management and background consolidation for efficient updates beyond active sessions. Through a storage-agnostic core API, LangMem integrates seamlessly with any backend and offers native compatibility with LangGraph’s long-term memory store, while also allowing type-safe memory consolidation using schemas defined in Pydantic. Developers can incorporate memory tools into agents using simple primitives to enable seamless memory creation, retrieval, and prompt optimization within conversational flows. -
7
Letta
Letta
Create, deploy, and manage your agents at scale with Letta. Build production applications backed by agent microservices with REST APIs. Letta adds memory to your LLM services to give them advanced reasoning capabilities and transparent long-term memory (powered by MemGPT). We believe that programming agents start with programming memory. Built by the researchers behind MemGPT, introduces self-managed memory for LLMs. Expose the entire sequence of tool calls, reasoning, and decisions that explain agent outputs, right from Letta's Agent Development Environment (ADE). Most systems are built on frameworks that stop at prototyping. Letta' is built by systems engineers for production at scale so the agents you create can increase in utility over time. Interrogate the system, debug your agents, and fine-tune their outputs, all without succumbing to black box services built by Closed AI megacorps.Starting Price: Free -
8
Naptha
Naptha
Naptha is a modular AI platform for autonomous agents that empowers developers and researchers to build, deploy, and scale cooperative multi‑agent systems on the agentic web. Its core innovations include Agent Diversity, which continuously upgrades performance by orchestrating diverse models, tools, and architectures; Horizontal Scaling, which supports collaborative networks of millions of AI agents; Self‑Evolved AI, where agents learn and optimize themselves beyond human‑designed capabilities; and AI Agent Economies, which enable autonomous agents to generate useful goods and services. Naptha integrates seamlessly with popular frameworks and infrastructure, LangChain, AgentOps, CrewAI, IPFS, NVIDIA stacks, and more, via a Python SDK that upgrades existing agent frameworks with next‑generation enhancements. Developers can extend or publish reusable components on the Naptha Hub, run full agent stacks anywhere a container can execute on Naptha Nodes. -
9
Cognee
Cognee
Cognee is an open source AI memory engine that transforms raw data into structured knowledge graphs, enhancing the accuracy and contextual understanding of AI agents. It supports various data types, including unstructured text, media files, PDFs, and tables, and integrates seamlessly with several data sources. Cognee employs modular ECL pipelines to process and organize data, enabling AI agents to retrieve relevant information efficiently. It is compatible with vector and graph databases and supports LLM frameworks like OpenAI, LlamaIndex, and LangChain. Key features include customizable storage options, RDF-based ontologies for smart data structuring, and the ability to run on-premises, ensuring data privacy and compliance. Cognee's distributed system is scalable, capable of handling large volumes of data, and is designed to reduce AI hallucinations by providing AI agents with a coherent and interconnected data landscape.Starting Price: $25 per month -
10
DemoGPT
Melih Ünsal
DemoGPT is an open source platform that simplifies the creation of LLM (Large Language Model) agents by providing an all-in-one toolkit. It offers tools, frameworks, prompts, and models for rapid agent development. The platform automatically generates LangChain code, which can be used for creating interactive applications with Streamlit. DemoGPT translates user instructions into functional applications through a multi-step process: planning, task creation, and code generation. It supports a streamlined approach to building AI-powered agents, offering an accessible environment for developing sophisticated, production-ready solutions with GPT-3.5-turbo. Additionally, it integrates API usage and external API interaction in future updates.Starting Price: Free -
11
VoltAgent
VoltAgent
VoltAgent is an open source TypeScript AI agent framework that enables developers to build, customize, and orchestrate AI agents with full control, speed, and a great developer experience. It provides a complete toolkit for enterprise-level AI agents, allowing the design of production-ready agents with unified APIs, tools, and memory. VoltAgent supports tool calling, enabling agents to invoke functions, interact with systems, and perform actions. It offers a unified API to seamlessly switch between different AI providers with a simple code update. It includes dynamic prompting to experiment, fine-tune, and iterate AI prompts in an integrated environment. Persistent memory allows agents to store and recall interactions, enhancing their intelligence and context. VoltAgent facilitates intelligent coordination through supervisor agent orchestration, building powerful multi-agent systems with a central supervisor agent that coordinates specialized agents.Starting Price: Free -
12
AgentSea
AgentSea
AgentSea is an open source platform designed to build, deploy, and share AI agents with ease. It delivers a collection of libraries and tools for building AI agent apps, favoring the UNIX philosophy of doing one thing well. Tools can be used individually or stacked together into a single agent app, and are compatible with frameworks like LlamaIndex and LangChain. Key components include SurfKit, a Kubernetes-style orchestrator for agents; DeviceBay, offering pluggable devices like file systems and desktops; ToolFuse, a library that wraps scripts, third-party apps, and APIs as Tool implementations; AgentD, a daemon making a Linux desktop OS accessible to bots; AgentDesk, a library for running AgentD-powered VMs; Taskara, for task management; ThreadMem, for building multi-role persistent threads; and MLLM, simplifying communication with multiple LLMs and multimodal LLMs. AgentSea also offers alpha agents like SurfPizza and SurfSlicer, which navigate GUIs using multimodal approaches.Starting Price: Free -
13
AgentForge
AgentForge
AgentForge is a comprehensive SaaS platform that streamlines the creation and customization of AI agents. It offers a fully integrated NextJS boilerplate, enabling users to build, deploy, and test AI applications efficiently. The platform includes pre-built AI agents, customizable graphs, reusable UI components, and an interactive playground for experimentation. AgentForge seamlessly integrates with popular AI tools such as Langchain, Langgraph, Langsmith, OpenAI, Groq, and Llamma, providing all the necessary building blocks for AI application development. With features like observability through Langsmith and over 20 themes via daisyUI, it caters to both small projects and more advanced needs. The platform's straightforward pricing model involves a one-time payment for lifetime access to all features, updates, and improvements, eliminating recurring subscription fees. AgentForge is designed to simplify AI development, making it accessible for developers and businesses.Starting Price: $99 per month -
14
RA.Aid
RA.Aid
RA.Aid is an open source AI assistant that autonomously handles research, planning, and implementation to expedite software development processes. Built on LangGraph's agent-based task execution framework, RA.Aid operates through a three-stage architecture. RA.Aid supports multiple AI providers, including Anthropic's Claude, OpenAI, OpenRouter, and Gemini, allowing users to select models that best fit their requirements. It also features web research capabilities, enabling the agent to pull real-time information from the internet to enhance its understanding and execution of tasks. It offers an interactive chat mode, allowing users to guide the agent directly, ask questions, or redirect tasks as needed. Additionally, RA.Aid integrates with 'aider' via the '--use-aider' flag to leverage specialized code editing capabilities. It is designed with a human-in-the-loop interaction mode, enabling the agent to seek user input during task execution to ensure higher accuracy.Starting Price: Free -
15
AI Crypto-Kit
Composio
AI Crypto-Kit empowers developers to build crypto agents by seamlessly integrating leading Web3 platforms like Coinbase, OpenSea, and more to automate real-world crypto/DeFi workflows. Developers can build AI-powered crypto automation in minutes, including applications such as trading agents, community reward systems, Coinbase wallet management, portfolio tracking, market analysis, and yield farming. The platform offers capabilities engineered for crypto agents, including fully managed agent authentication with support for OAuth, API keys, JWT, and automatic token refresh; optimization for LLM function calling to ensure enterprise-grade reliability; support for over 20 agentic frameworks like Pippin, LangChain, and LlamaIndex; integration with more than 30 Web3 platforms, including Binance, Aave, OpenSea, and Chainlink; and SDKs and APIs for agentic app interactions, available in Python and TypeScript. -
16
Mastra AI
Mastra AI
Mastra is a powerful TypeScript framework for building intelligent AI agents that can execute tasks, access knowledge bases, and maintain memory persistently within workflows. This framework simplifies the process of creating and deploying AI-powered agents by leveraging TypeScript’s capabilities to streamline development. With features like customizable agent instructions, memory, and task orchestration, Mastra provides developers with the tools to build and scale AI agents for various applications, from personal assistants to specialized domain experts.Starting Price: Free -
17
Pylar
Pylar
Pylar is a secure data-access layer that sits between AI agents and your databases, enabling agents to safely interact with structured data without giving them direct database access. It connects to one or more data sources (like BigQuery, Snowflake, PostgreSQL, business apps such as HubSpot or Google Sheets). Pylar can create governed SQL views using its built-in SQL IDE; those views define exactly which tables, columns, and rows agents are allowed to access. It lets you build “MCP tools” (either by writing natural-language prompts or manual configuration) that wrap SQL queries into standardized, safe operations. Agents can access data through a single MCP endpoint, compatible with multiple agent builders like custom AI assistants, no-code automation tools, or integrations (e.g. Zapier, n8n, LangGraph, VS Code, etc.).Starting Price: $20 per month -
18
Google Agentspace
Google
Unlock enterprise expertise for employees with agents that bring together Gemini’s advanced reasoning, Google-quality search, and enterprise data, regardless of where it’s hosted. Get your agents to access all your connected data, applications, and the freshest knowledge from the internet. Google Agentspace offers pre-built connectors for the most commonly used applications* in the enterprise so you can save time when you need quick answers or actions by doing them right from your Agentspace experience. Google Agentspace gives employees a single, company-branded multimodal search agent that acts as a central source of enterprise truth for your entire organization. Building on the best of Google’s search capabilities, Agentspace can provide conversational assistance, answer complex questions, make proactive suggestions and take actions based on your company’s unique information. Google Agentspace can do this across both unstructured data – such as documents and emails. -
19
Strands Agents
Strands Agents
Strands Agents is a lightweight, code-first framework for building AI agents, designed to simplify agent development by leveraging the reasoning capabilities of modern language models. Developers can create agents with just a few lines of Python code, defining a prompt and a list of tools, allowing the agent to autonomously execute complex tasks. It supports multiple model providers, including Amazon Bedrock (defaulting to Claude 3.7 Sonnet), Anthropic, OpenAI, and more, offering flexibility in model selection. Strands Agents features a customizable agent loop that processes user input, decides on tool usage, executes tools, and generates responses, supporting both streaming and non-streaming interactions. Built-in tools and the ability to add custom tools enable agents to perform a wide range of actions beyond simple text generation.Starting Price: Free -
20
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. -
21
AI-Q NVIDIA Blueprint
NVIDIA
Create AI agents that reason, plan, reflect, and refine to produce high-quality reports based on source materials of your choice. An AI research agent, informed by many data sources, can synthesize hours of research in minutes. The AI-Q NVIDIA Blueprint enables developers to build AI agents that use reasoning and connect to many data sources and tools to distill in-depth source materials with efficiency and precision. Using AI-Q, agents summarize large data sets, generating tokens 5x faster and ingesting petabyte-scale data 15x faster with better semantic accuracy. Multimodal PDF data extraction and retrieval with NVIDIA NeMo Retriever, 15x faster ingestion of enterprise data, 3x lower retrieval latency, multilingual and cross-lingual, reranking to further improve accuracy, and GPU-accelerated index creation and search. -
22
Microsoft Foundry Agent Service
Microsoft
Microsoft Foundry Agent Service is a secure, enterprise-ready platform for designing, deploying, and orchestrating AI agents at scale. It gives teams a streamlined interface and toolset to automate complex workflows using multi-agent systems. Developers can build with hosted agents, custom code, or agent frameworks while taking advantage of Azure’s reliability, scalability, and integrated observability. Built-in tools, enterprise connectors, and Model Context Protocol support make it easy for agents to interact with business systems and organizational data. Security, access governance, and compliance are embedded throughout, allowing companies to maintain full control while deploying intelligent automation across critical processes. With one-click deployment to Microsoft 365 experiences, Foundry Agent Service accelerates how organizations operationalize AI in everyday work. -
23
Complete
Complete
Complete is a collaborative AI workspace that enables teams and AI agents to work side by side in a unified environment designed to execute real workflows from planning to delivery. It centralizes conversations, files, and outputs into a single source of truth so teams can maintain shared context while agents perform tasks such as debugging, documenting, testing code, or generating business deliverables. It introduces structured execution threads that allow agents to run outcome-driven tasks while teams monitor progress and iterate on real outputs. Complete supports running multiple AI models in parallel, enabling specialized agents for coding, testing, and reasoning to operate within the same workflow. It integrates with project management and development tools and can bring AI directly into the IDE to accelerate coding and collaboration.Starting Price: $25 per month -
24
NVIDIA Agent Toolkit
NVIDIA
NVIDIA Agent Toolkit is a solution stack designed to build, deploy, and scale autonomous AI agents that can reason, plan, and execute complex tasks across enterprise systems. Unlike traditional generative AI, which responds to single prompts, agentic AI uses sophisticated reasoning and iterative planning to solve multi-step problems independently, enabling systems to analyze data, develop strategies, and complete workflows without continuous human input. It integrates multiple components of the NVIDIA AI ecosystem, including pretrained models, microservices, and development frameworks, allowing organizations to create context-aware AI agents that operate using their own data. These agents can ingest large volumes of structured and unstructured data from enterprise systems, interpret context, and coordinate actions across applications to automate processes such as customer service, software development, analytics, and operational workflows. -
25
Teradata Enterprise AgentStack
Teradata
Teradata Enterprise AgentStack is an integrated platform for building, deploying, and governing enterprise-grade autonomous AI agents that connect to trusted data and analytics, helping organizations move from experimentation to production-ready agentic AI with enterprise-level control. It unifies capabilities to support the full agent lifecycle; AgentBuilder accelerates the creation of intelligent agents using no-code and pro-code tools that integrate with Teradata Vantage and open-source frameworks; the Enterprise MCP delivers secure, context-rich access to governed enterprise data and curated prompts for agent intelligence; AgentEngine provides scalable execution of agents with consistent memory and reliability across hybrid environments; and AgentOps centralizes monitoring, governance, compliance, auditability, and policy enforcement so agents operate within defined guardrails. -
26
QVeris
QVeris AI
QVeris is an AI agent infrastructure for developers, designed for MCP and Skills-based agents. It provides a unified API to discover, access, and execute 10,000+ real-world tools, APIs, and data sources—enabling LLMs and AI agents to reason, retrieve data, and take real-world actions at scale. -
27
kagent
kagent
kagent is an open source, cloud-native AI agent framework designed to let teams build, deploy, and run autonomous AI agents directly inside Kubernetes clusters to automate complex operational tasks, troubleshoot cloud-native systems, and manage workloads without constant human intervention. It enables DevOps and platform engineers to create intelligent agents that understand natural language, plan, reason, and execute multi-step actions across Kubernetes environments using built-in tools and Model Context Protocol (MCP)-compatible tool integrations for functions like querying metrics, displaying pod logs, managing resources, and interacting with service meshes. It supports multiple model providers (such as OpenAI, Anthropic, and others), agent-to-agent communication for orchestrating sophisticated workflows, and observability features that help teams monitor agent behavior and performance.Starting Price: Free -
28
HappyRobot
HappyRobot
HappyRobot is an AI-native operating system designed to power autonomous operations by orchestrating customizable “AI workers” that understand your business, make intelligent decisions, and act in real time. Built to streamline enterprise workflows, especially in logistics, supply chain, retail, and services, it lets you create AI agents that can speak, type, reason, negotiate, schedule, process documents, browse systems, and escalate when needed. These workers execute tasks across voice calls, emails, messages, and other channels, with advanced reasoning powered by large language models connected to your tools and workflows via APIs, webhooks, or browser agents. You manage this AI workforce from a centralized “control tower,” where you can deploy, monitor, and iterate workflows in natural language or through integrated UIs, gaining visibility into each task and decision. -
29
Smolagents
Smolagents
Smolagents is an AI agent framework developed to simplify the creation and deployment of intelligent agents with minimal code. It supports code-first agents where agents execute Python code snippets to perform tasks, offering enhanced efficiency compared to traditional JSON-based approaches. Smolagents integrates with large language models like those from Hugging Face, OpenAI, and others, enabling developers to create agents that can control workflows, call functions, and interact with external systems. The framework is designed to be user-friendly, requiring only a few lines of code to define and execute agents. It features secure execution environments, such as sandboxed spaces, for safe code running. Smolagents also promotes collaboration by integrating deeply with the Hugging Face Hub, allowing users to share and import tools. It supports a variety of use cases, from simple tasks to multi-agent workflows, offering flexibility and performance improvements. -
30
mcp-use
mcp-use
mcp-use is an open source development platform offering SDKs, cloud infrastructure, and a developer-friendly control plane for building, managing, and deploying AI agents that leverage the Model Context Protocol (MCP). It enables connection to multiple MCP servers, each exposing specific tool capabilities like browsing, file operations, or specialized integrations, through a unified MCPClient. Developers can create custom agents (via MCPAgent) that dynamically select the most appropriate server for each task using configurable pipelines or a built-in server manager. It simplifies authentication, access control, audit logging, observability, sandboxed runtime environments, and deployment workflows, whether self-hosted or managed, making MCP development production-ready. With integrations for popular frameworks like LangChain (Python) and LangChain.js (TypeScript), mcp-use accelerates the creation of tool-enabled AI agents.Starting Price: Free -
31
CAMEL-AI
CAMEL-AI
CAMEL-AI is the first LLM-based multi-agent framework and an open-source community dedicated to exploring the scaling laws of agents. It enables the creation of customizable agents using modular components tailored for specific tasks, facilitating the development of multi-agent systems that address challenges in autonomous cooperation. The framework serves as a generic infrastructure for various applications, including task automation, data generation, and world simulations. By studying agents on a large scale, CAMEL-AI.org aims to gain valuable insights into their behaviors, capabilities, and potential risks. The community emphasizes rigorous research, balancing urgency with patience, and encourages contributions that enhance infrastructure, improve documentation, and implement research ideas. The platform offers components such as models, tools, memory, and prompts to empower agents, and supports integrations with various external tools and services. -
32
ServiceNow AI Agents
ServiceNow
ServiceNow's AI Agents are autonomous systems embedded within the Now Platform, designed to perform repetitive tasks traditionally handled by humans. These agents interact with their environment to collect data, make decisions, and execute tasks, enhancing efficiency over time. Leveraging domain-specific large language models and a robust reasoning engine, they possess a deep understanding of business contexts, enabling continuous improvement in outcomes. Operating natively across workflows and data systems, AI Agents facilitate end-to-end automation, boosting team productivity by orchestrating workflows, integrations, and actions throughout the enterprise. Organizations can deploy prebuilt AI agents or develop custom agents tailored to specific needs, all functioning seamlessly on the Now Platform. This integration allows employees to focus on more strategic initiatives by automating routine tasks. -
33
AgentFlow
Multimodal
AgentFlow is an agentic AI platform that automates workflows for finance and insurance companies. The platform includes modular AI agents, such as Document AI, Decision AI, and Report AI, each specializing in different stages of regulated workflows: triage, diligence, decisioning, and reporting. AgentFlow orchestrates multiple AI agents with human supervisors and third-party systems, enabling deep transformation of how work gets done. The platform features self-learning capabilities that allow AI agents to improve over time based on subject matter experts' feedback and provides transparency through explainability features that help users understand the reasoning behind AI-driven decisions. Every action and output is fully auditable, ensuring compliance with the strict standards of regulated industries. Its main mission is to codify tacit internal knowledge in order to reliably augment high-leverage workflows and preserve the know-how across generations of talent. -
34
AgentOps
AgentOps
Industry-leading developer platform to test and debug AI agents. We built the tools so you don't have to. Visually track events such as LLM calls, tools, and multi-agent interactions. Rewind and replay agent runs with point-in-time precision. Keep a full data trail of logs, errors, and prompt injection attacks from prototype to production. Native integrations with the top agent frameworks. Track, save, and monitor every token your agent sees. Manage and visualize agent spending with up-to-date price monitoring. Fine-tune specialized LLMs up to 25x cheaper on saved completions. Build your next agent with evals, observability, and replays. With just two lines of code, you can free yourself from the chains of the terminal and instead visualize your agents’ behavior in your AgentOps dashboard. After setting up AgentOps, each execution of your program is recorded as a session and the data is automatically recorded for you.Starting Price: $40 per month -
35
MaxClaw
MiniMax
MaxClaw is a managed AI agent deployment environment created by MiniMax that allows users to launch autonomous AI agents instantly without needing to configure servers, infrastructure, or maintenance. It is designed to simplify the process of building and running intelligent agents by providing an always-on environment where agents can execute tasks, interact with tools, and respond to requests continuously. MaxClaw integrates with the broader MiniMax Agent ecosystem, which uses advanced AI models capable of multi-step planning, reasoning, and task execution across complex workflows. Instead of manually deploying agent frameworks or maintaining cloud infrastructure, users can deploy an operational AI agent within seconds, allowing the system to handle tasks such as automation, research, content generation, coding, or data analysis. -
36
Lux
OpenAGI Foundation
Lux is a powerful computer-use AI platform that enables agents to operate software just like a human user—clicking, typing, navigating, and completing tasks across any interface. It offers three execution modes—Tasker, Actor, and Thinker—giving developers the ability to choose between step-by-step precision, near-instant task execution, or long-form reasoning for complex workflows. Lux can autonomously perform actions such as crawling Amazon data, running automated QA tests, or extracting insights from Nasdaq’s insider activity pages. The platform makes it possible to prototype and deploy real computer-use agents in as little as 20 minutes using developer-friendly SDKs and templates. Its agents are built to understand vague goals, execute long-running operations, and interact naturally with human-facing software instead of relying solely on APIs. Lux represents a new paradigm where AI goes beyond reasoning and content generation to directly operate computers at scale.Starting Price: Free -
37
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 -
38
Project Mariner
Google DeepMind
Project Mariner is a research prototype developed by Google DeepMind, built upon their advanced AI model, Gemini 2.0. It explores the future of human-agent interaction by automating tasks within a user's browser. Leveraging multimodal understanding, Project Mariner comprehends and reasons across various browser elements, including text, code, images, and forms. This enables it to navigate complex websites, automate repetitive tasks, and provide visual feedback to users. The system can interpret voice instructions and offers updates on task progress, ensuring users remain informed and in control. Additionally, Project Mariner can follow complex instructions by breaking them down into actionable steps, understanding relationships between web elements, and providing clear plans and actions to users. Currently, Project Mariner is in the testing phase with a select group of trusted users. Those interested in participating can join the waitlist for future testing opportunities. -
39
913.ai
913.ai
Empower your teams with AI Agents and explore next-generation efficiency. We enable deploying custom agents in no time, customized, integrated and impactful. Use customized solutions within a few days live in production via our proprietary infrastructure. Focus on your core business while we run and maintain your AI solution cost-efficient. Our agents can take over hundreds of use cases in high-stakes environments where complex reasoning and accuracy are essential. Automatically draft reference letters for your employees. Automate your Inbox based on custom labels. With Neurons, we can automate any document-related task, build agents, and process documents. Neurons are intelligent and can be seamlessly connected to other tools. With 913.ai, organizations in sectors such as insurance, logistics, legal, and beyond can accurately automate office work with the option of keeping humans in the loop for added oversight. This allows them to focus on more important work. -
40
Flowise
Flowise AI
Flowise is an open-source platform that enables developers and teams to build AI agents and LLM-powered applications through a visual interface. The platform provides modular building blocks that allow users to create everything from simple chatbot workflows to complex multi-agent systems. With its drag-and-drop design environment, developers can rapidly prototype and deploy AI-powered applications without extensive coding. Flowise supports integrations with more than 100 large language models, embeddings, and vector databases. It also includes features such as human-in-the-loop workflows, observability tools, and execution tracing for monitoring agent behavior. Developers can extend applications through APIs, SDKs, and embedded chat interfaces using TypeScript or Python. By combining visual development tools with scalable infrastructure, Flowise simplifies the process of building and deploying production-ready AI agents.Starting Price: Free -
41
Phidata
Phidata
Phidata is an open source platform for building, deploying, and monitoring AI agents. It enables users to create domain-specific agents with memory, knowledge, and external tools, enhancing AI capabilities for various tasks. The platform supports a range of large language models and integrates seamlessly with different databases, vector stores, and APIs. Phidata offers pre-configured templates to accelerate development and deployment, allowing users to quickly go from building agents to shipping them into production. It includes features like real-time monitoring, agent evaluations, and performance optimization tools, ensuring the reliability and scalability of AI solutions. Phidata also allows developers to bring their own cloud infrastructure, offering flexibility for custom setups. The platform provides robust support for enterprises, including security features, agent guardrails, and automated DevOps for smoother deployment processes.Starting Price: Free -
42
Agent S
Simular
Agent S is an open-source agentic framework built to enable autonomous computer use through an Agent-Computer Interface (ACI). It allows AI agents to operate graphical user interfaces similarly to humans by perceiving screens, reasoning through objectives, and executing actions across macOS, Windows, and Linux systems. The latest release, Agent S3, achieves state-of-the-art results on the OSWorld benchmark and surpasses human-level performance in complex multi-step computer tasks. By combining powerful foundation models such as GPT-5 with grounding models like UI-TARS, the framework translates visual inputs into accurate executable commands. Agent S supports multiple deployment options, including CLI, SDK, and cloud environments. It integrates seamlessly with leading model providers such as OpenAI, Anthropic, Gemini, Azure, and Hugging Face endpoints. -
43
OWL
CAMEL-AI
OWL (Optimized Workforce Learning) is an advanced framework designed for multi-agent collaboration in real-world task automation. Built on the CAMEL-AI platform, OWL aims to revolutionize AI agent interactions, enabling more efficient, natural, and resilient task automation across various industries. It achieves high performance, ranking #1 among open-source frameworks on the GAIA benchmark with a score of 58.18. OWL features real-time information sharing, dynamic task management, and integration with various tools and platforms, supporting collaborative AI agents in completing complex tasks.Starting Price: Free -
44
Qwen3.5
Alibaba
Qwen3.5 is a next-generation open-weight multimodal large language model designed to power native vision-language agents. The flagship release, Qwen3.5-397B-A17B, combines a hybrid linear attention architecture with sparse mixture-of-experts, activating only 17 billion parameters per forward pass out of 397 billion total to maximize efficiency. It delivers strong benchmark performance across reasoning, coding, multilingual understanding, visual reasoning, and agent-based tasks. The model expands language support from 119 to 201 languages and dialects while introducing a 1M-token context window in its hosted version, Qwen3.5-Plus. Built for multimodal tasks, it processes text, images, and video with advanced spatial reasoning and tool integration. Qwen3.5 also incorporates scalable reinforcement learning environments to improve general agent capabilities. Designed for developers and enterprises, it enables efficient, tool-augmented, multimodal AI workflows.Starting Price: Free -
45
LobeHub
LobeHub
LobeHub is an open-source AI platform that lets users create, customize, and manage AI agents and assistant teams that grow with their needs, enabling collaboration across workflows and projects with shared context and adaptive behavior. It supports multiple AI models and providers through an intuitive interface, allowing seamless switching and conversations across models while integrating knowledge bases, plugins, and task-specific skills for enhanced productivity. Users can deploy private chat applications and assistants, connect agents to real-world tools and data sources, and organize work into projects, schedules, and workspaces with coordinated agents executing tasks in parallel. LobeHub emphasizes long-term co-evolution between humans and agents through personal memory and continual learning, offering extensible frameworks for multimodal interaction and community contributions, such as an agent marketplace and plugin ecosystem.Starting Price: $9.90 per month -
46
KaibanJS
KaibanJS
KaibanJS is a JavaScript framework for building and visualizing multi‑agent AI systems using a familiar Kanban‑style interface. After installing via npm or npx and importing core classes, you can define agent goals, tasks, and teams programmatically, then run workflows locally or deploy to platforms like Vercel or AWS, no vendor lock‑in thanks to its MIT license. A Trello‑like Kaiban Board transforms console logs into shareable, real‑time workflows, while its Redux‑inspired state management ensures consistent handling of agent states, tasks, and results. Built‑in observability captures every state change, tool call, and log for easy debugging and performance monitoring, and extensibility comes via integrations with major frameworks, multiple LLM providers, language‑chain‑compatible tools, and custom plugins. Lightweight and framework‑agnostic, KaibanJS lets JavaScript developers orchestrate, monitor, and iterate on complex agentic workflows. -
47
Claude Sonnet 4.5
Anthropic
Claude Sonnet 4.5 is Anthropic’s latest frontier model, designed to excel in long-horizon coding, agentic workflows, and intensive computer use while maintaining safety and alignment. It achieves state-of-the-art performance on the SWE-bench Verified benchmark (for software engineering) and leads on OSWorld (a computer use benchmark), with the ability to sustain focus over 30 hours on complex, multi-step tasks. The model introduces improvements in tool handling, memory management, and context processing, enabling more sophisticated reasoning, better domain understanding (from finance and law to STEM), and deeper code comprehension. It supports context editing and memory tools to sustain long conversations or multi-agent tasks, and allows code execution and file creation within Claude apps. Sonnet 4.5 is deployed at AI Safety Level 3 (ASL-3), with classifiers protecting against inputs or outputs tied to risky domains, and includes mitigations against prompt injection. -
48
Lyzr
Lyzr AI
Lyzr Agent Studio is a low-code/no-code platform for enterprises to build, deploy, and scale AI agents with minimal technical complexity. Built on Lyzr's robust Agent Framework - the first and only agent framework to have safe and responsible AI natively integrated into the core agent architecture, this platform allows you to build AI Agents while keeping enterprise-grade safety and reliability in mind. The platform allows both technical and non-technical users to create AI-powered solutions that drive automation, improve operational efficiency, and enhance customer experiences—without the need for extensive coding expertise. Whether you're deploying AI agents for Sales, Marketing, HR, or Finance, or building complex, industry-specific applications for sectors like BFSI, Lyzr Agent Studio provides the tools to create agents that are both highly customizable and compliant with enterprise-grade security standards.Starting Price: $19/month/user -
49
OpenAGI
OpenAGI
OpenAGI is a developer-focused framework designed to help teams build autonomous, human-like AI agents capable of planning, reasoning, and executing tasks independently. It bridges the gap between traditional LLM applications and fully autonomous agents by offering tools for decision-making, continual learning, and long-term task execution. The platform allows developers to create specialized agents for real-world use cases across industries such as education, finance, healthcare, and software development. With its flexible architecture, OpenAGI supports sequential, parallel, and dynamic communication patterns between agents. Developers can choose automated configuration generation or manually tailor every detail for complete customization. OpenAGI represents an early but significant step toward making powerful, adaptive agent technology accessible to everyone.Starting Price: Free -
50
OpenAI Frontier
OpenAI
OpenAI Frontier is a new enterprise AI agent platform that helps businesses build, deploy, manage, and orchestrate fleets of AI agents that can perform real work inside existing systems, workflows, and data environments. It provides a unified framework where organizations can integrate AI agents, whether created by OpenAI or third parties, connect them with internal tools like CRM, data warehouses, ticketing systems, and other enterprise applications, and give them shared context, permissions, memory, and oversight so they can act reliably on business-relevant tasks. Frontier’s goal is to move AI agents from isolated pilots into production by providing features like shared business context, governance controls, onboarding workflows, observability, and secure access boundaries while allowing companies to centralize and scale intelligent automation in a way similar to how HR systems manage human work.
