Alternatives to Agent Builder
Compare Agent Builder alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Agent Builder in 2026. Compare features, ratings, user reviews, pricing, and more from Agent Builder competitors and alternatives in order to make an informed decision for your business.
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Gemini Enterprise Agent Platform is a comprehensive solution from Google Cloud designed to help organizations build, scale, govern, and optimize AI agents. It represents the evolution of Vertex AI, combining advanced model development with new capabilities for agent orchestration and integration. The platform provides access to over 200 leading AI models, including Google’s Gemini series and third-party options like Anthropic’s Claude. It enables teams to create intelligent agents using both low-code and code-first development environments. With features like Agent Runtime and Memory Bank, businesses can deploy long-running agents that retain context and perform complex workflows. The platform emphasizes security and governance through tools like Agent Identity, Agent Registry, and Agent Gateway. It also includes optimization tools such as simulation, evaluation, and observability to ensure consistent agent performance.
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StackAI
StackAI
StackAI is an enterprise AI automation platform to build end-to-end internal tools and processes with AI agents in a fully compliant and secure way. Designed for large, regulated organizations, it enables teams to automate complex workflows across operations, compliance, finance, IT, and support without heavy engineering. With StackAI you can: • Connect knowledge bases (SharePoint, Confluence, Notion, Google Drive, databases) with versioning, citations, and access controls • Publish AI agents as chat assistants, advanced forms, or APIs integrated into Slack, Teams, Salesforce, HubSpot, or ServiceNow • Govern usage with enterprise security: SSO (Okta, Azure AD, Google), RBAC, audit logs, PII masking, data residency, and cost controls • Route across OpenAI, Anthropic, Google, or local LLMs with guardrails, evaluations, and testing • Deploy in multi-tenant cloud, dedicated cloud, private cloud, or on-premise -
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n8n
n8n
Build complex automations 10x faster, without fighting APIs. Your days spent slogging through a spaghetti of scripts are over. Use JavaScript when you need flexibility and UI for everything else. n8n allows you to build flexible workflows focused on deep data integration. And with sharable templates and a user-friendly UI, the less technical people on your team can collaborate on them too. Unlike other tools, complexity is not a limitation. So you can build whatever you want — without stressing over budget. Connect APIs with no code to automate basic tasks. Or write vanilla Javascript when you need to manipulate complex data. You can implement multiple triggers. Branch and merge your workflows. And even pause flows to wait for external events. Interface easily with any API or service with custom HTTP requests. Avoid breaking live workflows by separating dev and prod environments with unique sets of auth data.Starting Price: $20 per month -
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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 -
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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 -
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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 -
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OpenAI Presence
OpenAI
OpenAI Presence is an enterprise product for deploying trusted AI agents across customer-facing and internal workflows. The platform helps organizations build voice and chat agents that can answer questions, resolve issues, use company systems, take approved actions, and escalate to human teams when needed. Presence combines model reasoning with policies, guardrails, standard operating procedures, simulations, evaluations, and escalation rules. Each deployment starts with a specific workflow, such as billing support, insurance claims, customer service, outbound sales, or employee IT requests. Codex-powered improvement workflows help teams review production sessions, identify gaps, test proposed updates, and approve controlled changes after launch. Built for eligible enterprise customers, OpenAI Presence helps companies put AI agents into production with reliability, governance, and deployment support from OpenAI teams and partners. -
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AgentKit
OpenAI
AgentKit is a unified suite of tools designed to streamline the process of building, deploying, and optimizing AI agents. It introduces Agent Builder, a visual canvas that lets developers compose multi-agent workflows via drag-and-drop nodes, set guardrails, preview runs, and version workflows. The Connector Registry centralizes the management of data and tool integrations across workspaces and ensures governance and access control. ChatKit enables frictionless embedding of agentic chat interfaces, customizable to match branding and experience, into web or app environments. To support robust performance and reliability, AgentKit enhances its evaluation infrastructure with datasets, trace grading, automated prompt optimization, and support for third-party models. It also supports reinforcement fine-tuning to push agent capabilities further.Starting Price: Free -
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Mistral Agents API
Mistral AI
Mistral AI has introduced its Agents API, a significant advancement aimed at enhancing the capabilities of AI by addressing the limitations of traditional language models in performing actions and maintaining context. This new API integrates Mistral's powerful language models with several key features, built-in connectors for code execution, web search, image generation, and Model Context Protocol (MCP) tools; persistent memory across conversations; and agentic orchestration capabilities. The Agents API complements Mistral's Chat Completion API by providing a dedicated framework that simplifies the implementation of agentic use cases, serving as the backbone of enterprise-grade agentic platforms. It enables developers to build AI agents capable of handling complex tasks, maintaining context, and coordinating multiple actions, thereby making AI more practical and impactful for enterprises. -
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Oracle AI Agent Platform
Oracle
Oracle AI Agent Platform is a fully-managed service that enables the creation, deployment, and management of intelligent virtual agents powered by large language models and integrated AI technologies. Agents can be set up through a simple few-step process, and can orchestrate tools such as natural‐language-to‐SQL conversion, retrieval-augmented generation from enterprise knowledge bases, custom function or API calling, and even the ability to coordinate sub-agents. They support multi-turn conversational experiences with context retention across sessions, enabling agents to handle follow‐up questions and maintain personalised, consistent interactions. Built-in guardrails help enforce content moderation, prompt-injection prevention, and protection of PII (personally identifiable information), while optional human-in-the-loop workflows allow real-time supervision and escalation.Starting Price: $0.003 per 10,000 transactions -
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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. -
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Microsoft Agent Framework
Microsoft
Microsoft Agent Framework is an open source SDK and runtime designed to help developers build, orchestrate, and deploy AI agents and multi-agent workflows using languages such as .NET and Python. It combines the simple agent abstractions of AutoGen with the enterprise-grade capabilities of Semantic Kernel, including session-based state management, type safety, middleware, telemetry, and broad model and embedding support, creating a unified platform for both experimentation and production use. It introduces graph-based workflows that give developers explicit control over how multiple agents interact, execute tasks, and coordinate complex processes, enabling structured orchestration across sequential, concurrent, or branching scenarios. It supports long-running and human-in-the-loop workflows through robust state management, allowing agents to maintain context, reason through multi-step problems, and operate continuously over time.Starting Price: Free -
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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. -
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Future AGI
Future AGI
Future AGI is an open-source, end-to-end AI agent engineering platform that covers the full lifecycle: simulate, evaluate, optimize, monitor, protect, gateway, and guardrail - all from one place. It helps teams ship self-improving AI agents by collapsing fragmented tooling into one platform and one feedback loop: simulate edge cases before launch, evaluate what happens in production, protect users in real time, and turn every trace into signal for the next version. Key capabilities include 70+ built-in evaluation templates covering quality, safety, factuality, RAG retrieval, bias, audio, and image evaluation, OpenTelemetry-native tracing, agent optimization, and real-time guardrails (PII detection, prompt injection blocking). SDKs are available in Python, TypeScript, Java, and C#, with integrations for OpenAI, LangChain, LlamaIndex, and 30+ frameworks. Apache 2.0 licensed, self-hostable or cloud-managed. -
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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 -
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Swarm
OpenAI
Swarm is an experimental, educational framework developed by OpenAI to explore ergonomic, lightweight multi-agent orchestration. It is designed to be scalable and highly customizable, making it suitable for scenarios involving a large number of independent capabilities and instructions that are challenging to encode into a single prompt. Swarm operates entirely on the client side and, like the Chat Completions API it utilizes, does not store state between calls. This stateless nature allows for the construction of scalable, real-world solutions without a steep learning curve. Swarm agents are distinct from assistants in the assistants API; they are named similarly for convenience but are otherwise completely unrelated. It includes examples demonstrating fundamentals such as setup, function calling, handoffs, and context variables, as well as more complex scenarios like a multi-agent setup for handling different customer service requests in an airline context.Starting Price: Free -
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Grok Voice Agent Builder
SpaceXAI
Grok Voice Agent Builder is xAI’s no-code platform for configuring production voice agents on Grok Voice in under two minutes. It is built for operators and developers who want high-volume voice agents without building the surrounding stack from scratch, bringing telephony, knowledge retrieval, tools, guardrails, MCPs, and observability into one place. Instead of stitching together separate speech-to-text, language model, and text-to-speech APIs, Voice Agent Builder uses one interface on a speech-to-speech path built for Grok Voice, tightly coupled to the model rather than assembled from three different systems. Users can write a plain-language description of how calls should flow, attach documents, connect tools, set guardrails, and move quickly from zero to a working agent. It can retrieve from uploaded knowledge bases in common formats such as plain text, Markdown, Word, PowerPoint, Excel, HTML, JSON, and others.Starting Price: $30 per month -
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AG2
AG2
AG2 is the open source AgentOS for building production-ready AI agents and multi-agent systems in minutes, not months. Formerly AutoGen, it provides an open source Python framework for building, orchestrating, and scaling AI agents that can collaborate through shared context, use tools, execute workflows, and support both autonomous and human-in-the-loop patterns. AG2 is designed for developers who want to build systems, not prompts, with simple and intuitive syntax, built-in conversation patterns, and a flexible platform for multi-agent automation. Agents in AG2 can extend their capabilities with tools, allowing them to interact with external systems, fetch real-time data, execute code, search the web, process documents, and complete complex tasks beyond a model’s internal knowledge. It supports many LLM providers and local models, including OpenAI-compatible endpoints, Anthropic Claude, Gemini through Vertex AI, DeepSeek, and LM Studio.Starting Price: Free -
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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 -
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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. -
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Upsonic
Upsonic
Upsonic is an open source framework that simplifies AI agent development for business needs. It enables developers to build, manage, and deploy agents with integrated Model Context Protocol (MCP) tools across cloud and local environments. Upsonic reduces engineering effort by 60-70% with built-in reliability features and service client architecture. It offers a client-server architecture that isolates agent applications, keeping existing systems healthy and stateless. It provides more reliable agents, scalability, and a task-oriented structure needed for completing real-world cases. Upsonic supports autonomous agent characterization, allowing self-defined goals and backgrounds, and integrates computer-use capabilities for executing human-like tasks. With direct LLM call support, developers can access models without abstraction layers, completing agent tasks faster and more cost-effectively. -
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Koog
JetBrains
Koog is a Kotlin‑based framework for building and running AI agents entirely in idiomatic Kotlin, supporting both single‑run agents that process individual inputs and complex workflow agents with custom strategies and configurations. It features pure Kotlin implementation, seamless Model Control Protocol (MCP) integration for enhanced model management, vector embeddings for semantic search, and a flexible system for creating and extending tools that access external systems and APIs. Ready‑to‑use components address common AI engineering challenges, while intelligent history compression optimizes token usage and preserves context. A powerful streaming API enables real‑time response processing and parallel tool calls. Persistent memory allows agents to retain knowledge across sessions and between agents, and comprehensive tracing facilities provide detailed debugging and monitoring.Starting Price: Free -
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Claude Agent SDK
Claude
The Claude Agent SDK is a developer toolkit that enables the creation of autonomous AI agents powered by Claude, allowing them to perform real-world tasks beyond simple text generation by interacting directly with files, systems, and tools. It provides the same underlying infrastructure used by Claude Code, including an agent loop, context management, and built-in tool execution, and is available for use in Python and TypeScript. With this SDK, developers can build agents that read and write files, execute shell commands, search the web, edit code, and automate complex workflows without needing to implement these capabilities from scratch. It maintains persistent context and state across interactions, enabling agents to operate continuously, reason through multi-step problems, take actions, verify results, and iterate until tasks are completed.Starting Price: Free -
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GraphBit
GraphBit
GraphBit is an enterprise-grade agentic AI framework built to run critical AI systems with security, governance, and predictable production performance. It combines a Rust execution core with a Python wrapper to give developers high-performance orchestration with the accessibility of Python, helping teams build reliable multi-agent workflows with minimal CPU and memory usage. GraphBit is designed around the layers that reduce risk, including interfaces, configuration, models, tools, actions, memory, orchestration, and observability. It integrates into existing apps, powers custom AI interfaces, and lets users interact through familiar workflows with controlled actions. Teams can define policies, rules, and guardrails centrally, while GraphBit enforces behavior without changing application code. It supports LLMs and multimodal models from multiple providers, allowing teams to swap models freely without breaking workflows or governance. -
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Cortex AgentiX
Palo Alto Networks
Cortex AgentiX is the next-generation evolution of Cortex XSOAR®, designed by Palo Alto Networks to securely build, deploy, and govern AI-powered security agents. It enables organizations to unleash agentic AI that acts as intelligent teammates, capable of planning and executing complex workflows around the clock. Cortex AgentiX is powered by over 1.2 billion real-world playbook executions, providing agents with proven operational intelligence. The platform offers a rich library of ready-to-use agents while also supporting custom, no-code agent creation tailored to specific security needs. With built-in guardrails, Cortex AgentiX ensures agents operate with the appropriate level of autonomy, including human-in-the-loop approvals for critical actions. Full transparency allows teams to trace every agent decision, action, and outcome for audit and compliance purposes. Cortex AgentiX integrates seamlessly across the Cortex ecosystem to help organizations stay ahead of evolving threats. -
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Intervo.ai
Intervo.ai
Intervo is an open source, enterprise-grade voice and chat AI agent platform designed to automate real-time customer interactions across voice and text channels. It allows businesses to build, train, and deploy custom agents in minutes without code; you define the agent’s purpose, upload domain knowledge (documents, files), choose a voice engine (e.g., ElevenLabs, Azure), and publish it to embedded channels. Its agents support use cases like lead qualification, customer support, AI receptionist/scheduling, interactive product assistance, and internal help agents (for HR, IT, etc.). They can integrate with telephony via Twilio, connect to multiple LLM backends (OpenAI, Claude, Gemini), orchestrate AI workflows, and embed on websites as widgets. It emphasizes scalability, compliance, and flexibility, letting organizations embed context-aware conversational agents that understand complex queries, route calls, and interact via speech or chat.Starting Price: $10 per month -
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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 -
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Ministral 3B
Mistral AI
Mistral AI introduced two state-of-the-art models for on-device computing and edge use cases, named "les Ministraux": Ministral 3B and Ministral 8B. These models set a new frontier in knowledge, commonsense reasoning, function-calling, and efficiency in the sub-10B category. They can be used or tuned for various applications, from orchestrating agentic workflows to creating specialist task workers. Both models support up to 128k context length (currently 32k on vLLM), and Ministral 8B features a special interleaved sliding-window attention pattern for faster and memory-efficient inference. These models were built to provide a compute-efficient and low-latency solution for scenarios such as on-device translation, internet-less smart assistants, local analytics, and autonomous robotics. Used in conjunction with larger language models like Mistral Large, les Ministraux also serve as efficient intermediaries for function-calling in multi-step agentic workflows.Starting Price: Free -
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II-Agent
Intelligent Internet
II-Agent is an open source intelligent assistant developed by Intelligent Internet, designed to enhance productivity across various domains such as research, content creation, data analysis, coding, automation, and problem-solving. It operates through a robust function-calling paradigm, driven by a powerful large language model (LLM), specifically Anthropic's Claude 3.7 Sonnet, and is supported by advanced planning, comprehensive execution capabilities, and intelligent context management. The agent's architecture includes a central reasoning and orchestration component that interfaces directly with the LLM, utilizing system prompting, interaction history management, and intelligent context management to maintain a coherent and efficient workflow. II-Agent's capabilities encompass multistep web search, source triangulation, structured note-taking, rapid summarization, blog and article drafting, lesson plan creation, creative prose, technical manuals, website creation, etc. -
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Claude Managed Agents
Anthropic
Claude Managed Agents is a pre-built, configurable agent system from Anthropic designed to run long-running, asynchronous tasks on managed infrastructure without requiring developers to build their own agent loops. It acts as a complete “agent harness,” allowing developers to define goals while the system handles execution, orchestration, and state management behind the scenes. Unlike direct model prompting, which requires step-by-step interaction, Managed Agents are designed for tasks that unfold over time, such as research, automation, or multi-step workflows, where the agent can continue working independently after being started. It supports advanced capabilities such as multi-agent orchestration, where a primary agent can coordinate specialized sub-agents that operate in parallel with isolated contexts, improving both speed and output quality. -
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AgentMonk
TechMonk
AgentMonk is an agentic AI customer engagement and automation platform that lets businesses build, deploy, and manage portfolios of AI agents that perceive, decide, and act across customer workflows to attract, interact, convert, and retain customers with personalized experiences powered by rich customer intelligence. It includes pre-built and custom AI agents for sales, support, reporting, segmentation, and more, plus a no-code agent builder and agentic workflows that automate complex tasks and unify customer data, segmentation, journey orchestration, and omnichannel engagement (Web, WhatsApp, Instagram, voice, email) in one full-stack toolkit. It provides enterprise-grade features such as strict guardrails, workflow observability, performance tracking, and security and compliance measures, enabling teams to test, observe, and optimize AI agent behavior and ensure high-quality interactions. -
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Agno
Agno
Agno is a lightweight framework for building agents with memory, knowledge, tools, and reasoning. Developers use Agno to build reasoning agents, multimodal agents, teams of agents, and agentic workflows. Agno also provides a beautiful UI to chat with agents and tools to monitor and evaluate their performance. It is model-agnostic, providing a unified interface to over 23 model providers, with no lock-in. Agents instantiate in approximately 2μs on average (10,000x faster than LangGraph) and use about 3.75KiB memory on average (50x less than LangGraph). Agno supports reasoning as a first-class citizen, allowing agents to "think" and "analyze" using reasoning models, ReasoningTools, or a custom CoT+Tool-use approach. Agents are natively multimodal and capable of processing text, image, audio, and video inputs and outputs. The framework offers an advanced multi-agent architecture with three modes, route, collaborate, and coordinate.Starting Price: Free -
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BabyAGI
BabyAGI
This Python script is an example of an AI-powered task management system. The system uses OpenAI and Chroma to create, prioritize, and execute tasks. The main idea behind this system is that it creates tasks based on the result of previous tasks and a predefined objective. The script then uses OpenAI's natural language processing (NLP) capabilities to create new tasks based on the objective, and Chroma to store and retrieve task results for context. This is a pared-down version of the original Task-Driven Autonomous Agent. The script works by running an infinite loop that does the following steps: 1. Pulls the first task from the task list. 2. Sends the task to the execution agent, which uses OpenAI's API to complete the task based on the context. 3. Enriches the result and stores it in Chroma. 4. Creates new tasks and reprioritizes the task list based on the objective and the result of the previous task.Starting Price: Free -
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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 -
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Airia
Airia
Airia’s enterprise AI orchestration platform seamlessly integrates with existing systems and data sources, offering a no-code agent builder for rapid prototyping, pre-built connectors for unified data integration, intelligent AI operations that optimize performance and costs through smart routing and centralized lifecycle management, and enterprise-grade security and governance with detailed audit capabilities and responsible AI guardrails. Model-agnostic and vendor-neutral, it supports flexible deployment across shared or dedicated cloud, private cloud, and on-premises environments, enabling both technical and business users to build, deploy, and manage secure AI agents at scale without complex installation or migration. Its intuitive interface and unified platform transform workflows across functions, from engineering and IT to finance, legal, marketing, sales, and support, so organizations can accelerate AI initiatives with confidence and compliance.Starting Price: $49 per month -
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Amazon Bedrock AgentCore
Amazon
Amazon Bedrock AgentCore enables you to deploy and operate highly capable AI agents securely at scale, offering infrastructure purpose‑built for dynamic agent workloads, powerful tools to enhance agents, and essential controls for real‑world deployment. It works with any framework and any foundation model in or outside of Amazon Bedrock, eliminating the undifferentiated heavy lifting of specialized infrastructure. AgentCore provides complete session isolation and industry‑leading support for long‑running workloads up to eight hours, with native integration to existing identity providers for seamless authentication and permission delegation. A gateway transforms APIs into agent‑ready tools with minimal code, and built‑in memory maintains context across interactions. Agents gain a secure browser runtime for complex web‑based workflows and a sandboxed code interpreter for tasks like generating visualizations.Starting Price: $0.0895 per vCPU-hour -
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Akka
Akka
Akka is a production-grade runtime and agentic AI platform built to make complex distributed systems reliable, resilient, and governable. The platform supports operational data processing, streaming, real-time analytics, long-running workflows, durable memory, edge coordination, digital twins, model inference, and agent execution. Akka combines actor-based concurrency, clustering, durable in-memory state, event sourcing, streaming, backpressure, and active-active high availability to support mission-critical workloads. Its Agentic AI Platform helps teams specify, generate, test, run, govern, and verify AI systems with agents, tools, orchestrations, integrations, memory, APIs, streaming, guardrails, evaluations, HITL workflows, and audit logging. Akka is designed to provide uniform governance, predictable pricing, cloud freedom, and reliability SLAs for enterprise AI and distributed applications. -
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Timbal
Timbal
Timbal is the end-to-end AI ecosystem for enterprises; a production AI platform that enterprise teams use to build, deploy, and govern agents, workflows, interfaces, and knowledge bases on the models they choose. Teams can define behavior in code or in Studio, run on the model and provider of their choice, and ship to chat, email, voice, and product UI from a single runtime. Timbal brings together the full production stack: a typed Python framework, a Studio for building visually, a runtime that orchestrates agents and workflows, governance and evals for enterprise rollout, and integrations with the systems teams already use. Agents provide autonomous AI for real work with reasoning, tools, and memory, while workflows create deterministic AI pipelines that chain steps, branch on logic, retry failed steps, stream outputs, and guarantee outcomes. Interfaces let teams ship custom AI experiences from chat to dashboards to voice, and knowledge bases connect company context.Starting Price: €25 per month -
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SuperAGI SuperCoder
SuperAGI
SuperAGI SuperCoder is an open-source autonomous system that combines AI-native dev platform & AI agents to enable fully autonomous software development starting with python language & frameworks SuperCoder 2.0 leverages LLMs & Large Action Model (LAM) fine-tuned for python code generation leading to one shot or few shot python functional coding with significantly higher accuracy across SWE-bench & Codebench As an autonomous system, SuperCoder 2.0 combines software guardrails specific to development framework starting with Flask & Django with SuperAGI’s Generally Intelligent Developer Agents to deliver complex real world software systems SuperCoder 2.0 deeply integrates with existing developer stack such as Jira, Github or Gitlab, Jenkins, CSPs and QA solutions such as BrowserStack /Selenium Clouds to ensure a seamless software development experienceStarting Price: Free -
40
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. -
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Superexpert.AI
Superexpert.AI
Superexpert.AI is an open source platform that enables developers to build advanced, multi-task AI agents without writing code. It supports the creation of versatile AI solutions, from simple chatbots to sophisticated agents capable of handling hundreds of tasks. It is extensible, allowing integration of custom tools and functions, and is compatible with various hosting providers, including Vercel, AWS, GCP, and Azure. Superexpert.AI offers features like Retrieval-Augmented Generation (RAG) for efficient document retrieval, multi-model compatibility with AI models such as OpenAI, Anthropic, and Gemini, and a modern web application architecture built with Next.js, TypeScript, and PostgreSQL. It provides a user-friendly interface for configuring agents and tasks, making it accessible for users without programming experience.Starting Price: Free -
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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 -
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Mistral AI Studio
Mistral AI
Mistral AI Studio is a unified builder-platform that enables organizations and development teams to design, customize, deploy, and manage advanced AI agents, models, and workflows from proof-of-concept through to production. The platform offers reusable blocks, including agents, tools, connectors, guardrails, datasets, workflows, and evaluations, combined with observability and telemetry capabilities so you can track agent performance, trace root causes, and govern production AI operations with visibility. With modules like Agent Runtime to make multi-step AI behaviors repeatable and shareable, AI Registry to catalogue and manage model assets, and Data & Tool Connections for seamless integration with enterprise systems, Studio supports everything from fine-tuning open source models to embedding them in your infrastructure and rolling out enterprise-grade AI solutions.Starting Price: $14.99 per month -
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Flowyte
Flowyte
Flowyte is an AI agent studio for phone and chat. Businesses describe what they do in plain English and Flowyte drafts an agent with a persona, goals, knowledge, Skills, and guardrails. Agents can answer calls and website chats 24/7, book appointments, qualify leads, collect caller information, answer common questions, send SMS, and route or warm-transfer conversations to a human when needed. Teams can test before publishing, review pre-flight reports, and inspect conversation receipts after each interaction. Flowyte supports 30+ languages, say-or-press keypad input, interruptions, and API-driven agent management. It is designed for small and midsize businesses in service industries such as HVAC, plumbing, healthcare, real estate, legal, restaurants, automotive, and franchises.Starting Price: $0/month; voice from $0.11/min -
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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. -
46
Xano
Xano
Xano is the unified backend for building and deploying production-grade apps and AI agents. Instead of stitching together databases, runtimes, APIs, auth, integrations, and monitoring—plus a separate orchestrator for agents—Xano provides everything in one secure, scalable platform. Teams can model data, compose logic, expose secure APIs, and integrate with any system, while AI agents can use data and APIs, call external tools, and run server-side with observability and guardrails. Build visually, with AI, or in code from your IDE, then deploy with one click and scale automatically. Xano works with any frontend, including Lovable, Bolt, WeWeb, Retool, and custom code, so you don’t need to rebuild as you grow. Compliance, reliability, and scaling are built-in, enabling teams to focus on the business logic that makes their software unique.Starting Price: Free -
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Thread AI
Thread AI
Thread AI’s Lemma is a composable AI orchestration platform that lets organizations build, connect, and manage secure, scalable AI-powered workflows and agents to automate complex, mission-critical processes without reinventing infrastructure. It provides builder-friendly interfaces, low-code building blocks, SDKs and APIs for engineering teams, and centralized observability and traceability for all workflows, enabling drag-and-drop creation of reusable AI “Workers” that integrate models, functions, and data from structured or unstructured sources. Lemma prioritizes security and compliance with enterprise-grade safeguards, including AES-256 encryption at rest, TLS in transit, governance controls, and configurable workflow guardrails to strip or redact sensitive data, while supporting on-cloud or on-premise deployment and automatic vulnerability scanning. -
48
AgentHub
AgentHub
AgentHub is a staging environment to simulate, trace, and evaluate AI agents in a private, sandboxed space that lets you ship with confidence, speed, and precision. With easy setup, you can onboard agents in minutes; a robust evaluation infrastructure provides multi-step trace logging, LLM graders, and fully customizable evaluations. Realistic user simulation employs configurable personas to model diverse behaviors and stress scenarios, and dataset enhancement synthetically expands test sets for comprehensive coverage. Prompt experimentation enables dynamic multi-prompt testing at scale, while side-by-side trace analysis lets you compare decisions, tool invocations, and outcomes across runs. A built-in AI Copilot analyzes traces, interprets results, and answers questions grounded in your own code and data, turning agent runs into clear, actionable insights. Combined human-in-the-loop and automated feedback options, along with white-glove onboarding and best-practice guidance. -
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Lunary
Lunary
Lunary is an AI developer platform designed to help AI teams manage, improve, and protect Large Language Model (LLM) chatbots. It offers features such as conversation and feedback tracking, analytics on costs and performance, debugging tools, and a prompt directory for versioning and team collaboration. Lunary supports integration with various LLMs and frameworks, including OpenAI and LangChain, and provides SDKs for Python and JavaScript. Guardrails to deflect malicious prompts and sensitive data leaks. Deploy in your VPC with Kubernetes or Docker. Allow your team to judge responses from your LLMs. Understand what languages your users are speaking. Experiment with prompts and LLM models. Search and filter anything in milliseconds. Receive notifications when agents are not performing as expected. Lunary's core platform is 100% open-source. Self-host or in the cloud, get started in minutes.Starting Price: $20 per month -
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BotDojo
BotDojo
BotDojo is an enterprise-grade AI enablement platform that empowers organizations to design, deploy, monitor, and scale intelligent agents across chat, voice, email, and web channels using a low-code visual workflow builder, while integrating deeply with enterprise data sources and systems. It provides over 100 ready-made templates to accelerate common use-cases (such as support automation, knowledge search, sales insights, and internal ops), supports branching logic, memory, tool orchestration (code, RPA, web browse), and connects to CRMs, ticketing systems, and databases. BotDojo also delivers human-feedback loops and continuous agent learning by enabling employees to coach agents via feedback queues, codifying corrections into memory and prompts, and evaluating performance through robust observability (audit trails, metrics such as deflection, first-contact resolution, and cost per interaction).Starting Price: $89 per month
