Alternatives to xpander.ai

Compare xpander.ai alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to xpander.ai in 2026. Compare features, ratings, user reviews, pricing, and more from xpander.ai competitors and alternatives in order to make an informed decision for your business.

  • 1
    Gemini Enterprise Agent Platform
    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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  • 2
    BAND

    BAND

    BAND.ai

    BAND builds enterprise-grade interaction infrastructure for distributed AI agents. Its platform enables real-time, multi-peer collaboration across agents and humans, while providing a runtime control plane that enforces policy, authority boundaries, and visibility across heterogeneous systems. BAND supports developers, engineering teams, and enterprise platform leaders operating multi-agent ecosystems across internal systems, SaaS platforms, and partner environments.
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  • 3
    MuleSoft Anypoint Platform
    MuleSoft is an agentic control plane designed to help enterprises govern, orchestrate, and secure AI agents, APIs, applications, models, and data across complex digital environments. The platform supports multi-agent governance, API management, integration, automation, and gateway federation from one unified control plane. With solutions such as MuleSoft Agent Fabric, MuleSoft Omni Gateway, Agent Registry, Agent Scanners, and Agent Broker, organizations can discover agents, manage interactions, reduce shadow AI, and coordinate workflows across ecosystems. MuleSoft also helps teams turn existing APIs and applications into governed tools that AI agents can safely discover and use. Its platform supports developers and business users with natural language development, prebuilt connectors, monitoring, API governance, and integration tools. MuleSoft is built to help enterprises scale AI adoption with stronger compliance, observability, security, and operational confidence.
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    Microsoft Foundry Agent Service
    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.
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    Vivgrid

    Vivgrid

    Vivgrid

    Vivgrid is a development platform for AI agents that emphasizes observability, debugging, safety, and global deployment infrastructure. It gives you full visibility into agent behavior, logging prompts, memory fetches, tool usage, and reasoning chains, letting developers trace where things break or deviate. You can test, evaluate, and enforce safety policies (like refusal rules or filters), and incorporate human-in-the-loop checks before going live. Vivgrid supports the orchestration of multi-agent systems with stateful memory, routing tasks dynamically across agent workflows. On the deployment side, it operates a globally distributed inference network to ensure low-latency (sub-50 ms) execution and exposes metrics like latency, cost, and usage in real time. It aims to simplify shipping resilient AI systems by combining debugging, evaluation, safety, and deployment into one stack, so you're not stitching together observability, infrastructure, and orchestration.
    Starting Price: $25 per month
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    CAMEL-AI

    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.
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    HelpNow Agentic AI Platform
    Bespin Global’s HelpNow Agentic AI Platform is an enterprise-grade AI agent automation and orchestration platform that lets organizations rapidly create, deploy, and manage autonomous AI agents tailored to real business workflows without deep coding, using a visual builder (Agentic Studio) and centralized portal to design single or multi-agent workflows, integrate with existing systems via APIs and connectors, and monitor performance in real time with an Agent Control Tower for governance, policy enforcement, and quality oversight; it supports LLM orchestration, multimodal inputs (text, voice, STT/TTS), and flexible deployment across cloud environments (AWS, GCP, Azure, on-premises) with connectivity to internal data, documents, and business processes so agents can act on context-rich enterprise information. It combines tools for agent lifecycle management, real-time observability, integration with voice and document processing, and enterprise governance.
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    Mistral AI Studio
    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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    Phinite

    Phinite

    Phinite AI

    Phinite provides shared infrastructure for building, deploying, and governing AI agents across orchestration, security, observability, lifecycle management, and environment promotion — so engineering teams don't rebuild these layers for every new agent use case. Core capabilities: Orchestration for multi-agent systems (agent-to-agent, nested calls) Deep session-level observability: execution timelines, decision variables, tool calls, latency/cost tracking Private Agent Registry for skill discoverability Eval suite for accuracy/safety benchmarking Dev-to-Production workflow with environment promotion Kubernetes-native deployment, VPC-internal deployability SOC 2 Type 2 compliance
    Starting Price: $20/month
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    AgentKit

    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.
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    VDF AI

    VDF AI

    VDF AI

    VDF AI is an enterprise AI agent platform that enables organizations to build, deploy, govern, and operate secure AI agents across on-premises, private-cloud, and cloud environments. The platform combines multi-agent orchestration, private retrieval-augmented generation (RAG), model registration and routing, governed tool execution, policy controls, auditability, and enterprise integrations. Organizations can connect approved local or cloud LLMs, create reusable agents and workflows, isolate data by company, department, or user, and retain control over sensitive information. VDF AI is designed for production use in regulated and data-sensitive environments, supporting human approval steps, role-based access, observability, and controlled deployment through containerized infrastructure. It helps enterprises move from isolated AI pilots to scalable, governed AI operations while reducing vendor lock-in and maintaining data sovereignty.
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    elsai

    elsai

    elsai

    elsai is a purpose-built agentic operations platform that gives regulated enterprises the infrastructure to run AI at production scale — not just in pilots. The platform combines three integrated layers: a domain intelligence layer trained to comprehend patient records, financial instruments, and regulatory documents; a multi-agent orchestration engine that sequences specialized agents across complex workflows; and ARMS, a full-observability governance framework that tracks every token, decision, and cost in real time. With 200+ pre-built enterprise integrations and a structured six-stage deployment path, elsai is production-ready for healthcare, BFSI, life sciences, and logistics — governed, auditable, and built on 16 years of enterprise delivery.
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    Maxim

    Maxim

    Maxim

    Maxim is an agent simulation, evaluation, and observability platform that empowers modern AI teams to deploy agents with quality, reliability, and speed. Maxim's end-to-end evaluation and data management stack covers every stage of the AI lifecycle, from prompt engineering to pre & post release testing and observability, data-set creation & management, and fine-tuning. Use Maxim to simulate and test your multi-turn workflows on a wide variety of scenarios and across different user personas before taking your application to production. Features: Agent Simulation Agent Evaluation Prompt Playground Logging/Tracing Workflows Custom Evaluators- AI, Programmatic and Statistical Dataset Curation Human-in-the-loop Use Case: Simulate and test AI agents Evals for agentic workflows: pre and post-release Tracing and debugging multi-agent workflows Real-time alerts on performance and quality Creating robust datasets for evals and fine-tuning Human-in-the-loop workflows
    Starting Price: $29/seat/month
  • 14
    Flowise

    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.
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    Subconscious

    Subconscious

    Subconscious

    Subconscious is a developer-first platform designed to build, deploy, and scale production-ready AI agents by handling the hardest parts of agent architecture automatically. It provides a complete agent system that manages context, orchestrates tools, and enables long-horizon reasoning, allowing developers to focus on defining goals and capabilities rather than stitching together complex infrastructure. It introduces a unified inference engine composed of a co-designed model and runtime that decomposes complex tasks, generates workflows dynamically, and executes multi-step reasoning without manual context engineering or multi-agent orchestration. Unlike traditional approaches that rely on chaining APIs and frameworks, Subconscious enables agents to take in goals and tools, then autonomously plan, reason, and act with minimal human intervention, effectively creating systems that can “get the job done” on their own.
    Starting Price: $2 per 1M tokens
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    Netguru Omega
    Omega is an internally developed AI agent integrated directly into Slack to supercharge sales workflows by handling routine tasks, surfacing insights, and nudging team members toward best practices, all with minimal friction. It seamlessly connects with core tools like Slack, Google Drive, Apollo, Salesforce, and transcript systems to automate time-consuming chores, generating call agendas, summarizing expert calls, locating relevant documents, and tracking deal progression. Omega operates as a modular, multi-agent system, utilizing specialized roles orchestrated via frameworks like AutoGen to plan, execute, and validate actions within the workflow. This architecture runs on a cloud-native, serverless stack using AWS Lambda and Step Functions, enabling flexibility and scale. Observability and iteration are supported through tools like Langfuse, Promptfoo, CI/CD pipelines, and Terraform.
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    21st

    21st

    21st.dev

    21st is a developer platform that provides the fastest way to add AI agents directly into applications. The platform offers an SDK that allows developers to define, deploy, and run AI agents with minimal infrastructure setup. Developers can integrate agents using popular frameworks such as Next.js, React, TypeScript, Python, and Node.js. 21st includes built-in features like chat interfaces, session history, tool execution, memory, and real-time streaming responses. The platform also manages backend components such as sandboxed execution environments, authentication, rate limits, and observability. With support for Claude Code and Codex runtimes, developers can build agents that interact with tools, files, and APIs securely. By handling infrastructure and deployment automatically, 21st enables teams to launch production-ready AI agents quickly.
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    elsai Foundry
    elsai Foundry is a governance-first platform to design, deploy, and operate AI agents for regulated enterprise workflows. It embeds compliance guardrails, PHI/PII redaction, prompt management, and real-time ARMS observability into every workflow. Its architecture spans multi-agent orchestration, policy and approvals enforcement, human-in-the-loop controls, domain intelligence, and pre-built agents across healthcare, life sciences, insurance, procurement, and supply chain.
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    HiClaw

    HiClaw

    AgentScope

    HiClaw is an open source multi-agent OS powered by Matrix. It lets multiple AI agents collaborate in Matrix rooms, fully visible to humans, with real-time intervention capability. A Manager Agent coordinates multiple Worker Agents to complete complex tasks, intelligently decomposing work and enabling parallel execution for stronger complex task handling. Built for enterprise-grade security and multi-agent collaboration, HiClaw uses the open Matrix IM protocol so all agent communications remain transparent, auditable, and suitable for distributed deployment and federation. Humans can enter any Matrix room at any time to observe agent conversations, intervene, or correct agent behavior in real time, ensuring safety and control. It's clear that a two-tier Manager-Worker architecture gives each agent distinct responsibilities and makes it easier to extend the system with custom Worker Agents for different scenarios.
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    DNotifier

    DNotifier

    DNotifier

    DNotifier has built the infrastructure layer for AI-native applications. As AI becomes a core part of modern software, developers face increasing complexity. Building production-ready AI systems often requires combining multiple services for agent orchestration, event streaming, knowledge retrieval, search, prompt testing, AI workflows, notifications, real-time communication, and scalable backend infrastructure. DNotifier brings these capabilities together into a unified platform designed specifically for AI-native software. Our platform enables developers to build autonomous AI agents, multi-agent systems, real-time applications, and intelligent workflows without stitching together dozens of disconnected tools. With a developer-first approach, DNotifier provides the infrastructure needed to power scalable, reliable, and event-driven AI applications from a single SDK and API. Our mission is to simplify the way SME's build intelligent software.
    Starting Price: $49/month
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    GraphBit

    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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    Melaya

    Melaya

    Melaya Labs LLC

    Melaya is a platform for building and running AI agents across business tools, browsers and Android apps, with six connected products: - Melaya Agents: A visual builder for workflows and multi-agent teams. Combines models, tools, memory, schedules and approval steps in replayable runs. - Melaya Assistant: One conversational workspace for working across connected business systems, using approved tools and shared context. - Melaya Device Control: AI agents that operate real Android apps through accessibility, without root or a dedicated API integration. - Melaya Browser Control: Agents that navigate and act inside your browser, with selected tabs, site permissions, live observation and manual takeover. - Melaya MCP Server: Gives existing AI assistants including Claude, ChatGPT and Cursor, access to Melaya’s tools, browser control, mobile agents and workflows through one connection. - Melaya Marketing: A unified suite for AI SEO audits, backlink building, advertising and analytics
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    OpenChiip Harness
    OpenChiip Harness is a self-hosted AI agent runtime and orchestration framework for developers building local or coordinated agent workflows. It combines LLM conversations, skill orchestration, tool execution, multi-layer memory, resource monitoring, and multi-agent collaboration in a React administration dashboard. Run it as a local service or connect it to the OpenChiip platform for collaborative scheduling. Its CLI, web dashboard, HTTP API, and WebSocket interface support chat, tools, sessions, memory, task management, and monitoring. It supports Baidu ERNIE, OpenAI-compatible model providers, and delegation to Codex or Claude Code. Install via pip or deploy with Docker, Linux packages, systemd, or Windows installers; macOS supports pip installation. Licensed under AIGCGPL-1.0.
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    VoltAgent

    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.
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    Agentspan

    Agentspan

    Agentspan

    Agentspan is an open source server and SDK designed to bring durable execution to AI agents, transforming how they run in real-world environments beyond simple demos. It allows developers to define agents in Python and compile them into persistent, crash-safe workflows where execution state lives on the server rather than in the local process, ensuring that work is never lost if a system crashes or restarts. This architecture enables agents to pause, resume, and continue from the exact step they left off, even when reconnected from a different machine. It supports human-in-the-loop workflows, allowing agents to halt for approval and resume seamlessly through interfaces like Slack, web portals, or code. It also enables multi-agent pipelines, where several agents can be chained together in a single expression, with each step logged, observable, and recoverable across the entire workflow.
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    Autoheal

    Autoheal

    Autoheal

    Autoheal actively investigates alerts, hypothesizes root cause, and proposes mitigating fixes under human supervision. It also automates the postmortem phase completely. At its core is the Production Context Graph (PCG), a continuously updating, living map that connects your infrastructure, application logic, production tools and tribal knowledge in real-time. The PCG is built through autonomous exploration of your observability, cloud and code stack, and iteratively refined by a Reinforcement Learning loop as you use Autoheal. On top of the PCG lies a Multi-Agent Platform of specialized agents that collaborate with humans to solve production problems safely and efficiently. For AI agents focused on production engineering to succeed in real-world enterprise deployments, three crucial gaps must be addressed. The Context Gap: can the AI navigate my organization’s fragmented context? The Trust Gap: can I trust the AI to strictly adhere to my organization’s security policies?
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    Microsoft Agent Framework
    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.
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    Origon

    Origon

    Origon

    Origon is a full-stack AI agent development and operations platform engineered as a unified “Agentic Operating System” that supports the entire lifecycle of autonomous AI systems from design to deployment and observability. It offers an intuitive Studio for visual, drag-and-drop agent creation and configuration, Sessions for real-time observation, behavior tracing, and debugging, and Insights dashboards for performance analytics, reliability tracking, and outcome measurement in one place. Origon runs natively on dedicated infrastructure optimized for low-latency performance and security, avoiding dependency on external cloud APIs, and includes a built-in knowledge engine that connects agents to contextual memory and domain data so responses stay grounded and consistent. It supports hundreds of connectors and APIs, including chat, voice, WhatsApp, SMS, email, and telephony, and lets agents execute code and interact with real systems with a single click.
    Starting Price: $200 per month
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    Inquir Compute

    Inquir Compute

    Inquir Compute

    Inquir Compute is a cloud platform for deploying and running server-side code without managing servers, Kubernetes, CI/CD, or DevOps infrastructure. It lets developers create functions, APIs, webhooks, cron jobs, background tasks, and multi-step workflows directly from a browser-based editor or API. Users can write code in Node.js, Python, or Go, configure runtime settings such as memory, CPU, timeout, environment variables, and network access, then deploy and invoke it in isolated containers. Functions can be exposed through an API Gateway, triggered manually, scheduled, or combined into pipelines where one step passes data to another. The platform is designed for long-running workloads such as AI agents, scraping, document processing, data enrichment, integrations, and automation. It includes logs, traces, invocation history, error tracking, route management, API keys, tenant isolation, and observability tools.
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    Agent Development Kit (ADK)
    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.
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    Claude Managed Agents
    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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    VibePaper

    VibePaper

    VibePaper

    VibePaper is an AI collaboration workbench for short drama and AI video production teams, built around a node-based, unlimited canvas where creators can plan, generate, and manage complex narrative projects in one visual space. It focuses on long-form, story-driven AI content with multi-agent collaboration, allowing different agents to handle separate creative stages such as scriptwriting, storyboard generation, character asset creation, model selection, and production planning. Instead of asking users to manually choose every model, VibePaper’s agent system can assign the most suitable model based on the task, supporting high-quality content generation with frontier models such as Sora 2, Veo 3.1, Seedance 2.0, and Nano Banana Pro. Its product logic is designed for creators who need more than fast single-shot video generation; it supports memory, role consistency, character continuity, and structured workflows for stories with recurring characters or longer runtimes.
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    Qoris AI

    Qoris AI

    Kardash AI Inc

    Qoris AI is a unified AI Operating System designed to replace fragmented tools with specialized agents that work together across the entire customer journey. It includes a live Sales Agent for lead conversion today, along with Knowledge and Service Agents in beta and a Thinking Agent™ launching in 2026 to orchestrate multi-agent strategies automatically. The platform enables businesses to convert visitors, answer internal questions from documents, automate 24/7 support, and soon, generate goal-driven plans through autonomous orchestration. Qoris AI requires no coding, deploys instantly, and is built with enterprise-grade security including SOC 2 and GDPR compliance. Designed as a scalable, multi-agent ecosystem, it allows teams to start with a single agent and expand into a full AI stack. With clear pricing, OS-level analytics, and seamless interoperability, Qoris AI becomes the central intelligence layer powering modern enterprise workflows.
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    Tile

    Tile

    Tile.dev

    Tile is an AI-powered platform that lets you design, build, and ship full-code, production-grade native iOS and Android apps in minutes without a full-stack dev team. Using conversational AI agents, Tile handles everything from UI layout and component logic to backend integrations, then generates clean, editable React Native code and deployable infrastructure so you can launch real apps without wrestling with DevOps. An intuitive visual editor provides live preview and drag-and-drop customization, while professional AI agents scaffold complex features, dynamic charts, personalized banners, deep links, analytics events, all wired up and styled with Tailwind CSS by default. Tile’s single-process workflow covers CI/CD, App Store and Play Store submission, and built-in observability for monitoring app health, freeing product and marketing teams to iterate at business speed and developers to focus on advanced logic.
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    AgentOps

    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
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    CrewAI

    CrewAI

    CrewAI

    CrewAI is a leading multi-agent platform that enables organizations to streamline workflows across various industries by building and deploying automated processes using any Large Language Model (LLM) and cloud platform. It offers a comprehensive suite of tools, including a framework and UI Studio, to facilitate the rapid development of multi-agent automations, catering to both coding professionals and those seeking no-code solutions. The platform supports flexible deployment options, allowing users to move their created 'crews'—teams of AI agents—to production with confidence, utilizing powerful tools for different deployment types and autogenerated user interfaces. CrewAI also provides robust monitoring capabilities, enabling users to track the performance and progress of their AI agents on both simple and complex tasks. Additionally, it offers testing and training tools to continually enhance the efficiency and quality of outcomes produced by these AI agents.
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    Calljmp

    Calljmp

    Calljmp

    Calljmp is a developer-first AI agent runtime designed to build, run, and scale long-running stateful workflows written in TypeScript. While many modern tools like Mastra AI provide rich frameworks to define agents and workflows, Calljmp focuses on actually running them reliably in production. Calljmp combines agent logic, durable execution, human-in-the-loop pause/resume, retries with idempotency, and built-in observability into a unified execution environment. Developers implement agents as code, and the runtime guarantees reliable execution, state persistence, and operational visibility without gluing together custom queues, databases, and monitoring stacks. Calljmp is ideal for engineering teams, product developers, and backend architects who want to embed intelligent agents into product systems while offloading execution complexity to a purpose-built runtime.
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    AG2

    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.
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    Agent Computer

    Agent Computer

    Agent Computer

    AgentComputer is a cloud-based infrastructure platform designed specifically for running AI agents in isolated, fully functional virtual environments. It provides “cloud computers” in the form of lightweight Ubuntu-based sandboxes that can be provisioned in under a second, allowing developers to quickly spin up, access, and manage environments through a command-line interface. These environments include persistent storage, meaning any installed tools, files, or configurations remain intact across restarts, enabling continuous and stateful workflows. It is built around an agent-first architecture, where AI agents can directly execute tasks within these environments via SSH, eliminating friction between instruction and execution. It includes an integrated AI harness that supports agents such as Claude, Codex, and other coding assistants, enabling collaborative, multi-agent workflows within the same system.
    Starting Price: $20 per month
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    Manifold Security

    Manifold Security

    Manifold Security

    Manifold Security is an AI Detection and Response platform built to secure autonomous AI agents operating on enterprise endpoints, addressing a critical gap in traditional cybersecurity approaches that focus primarily on user activity or model inputs and outputs. It provides runtime visibility into what AI agents actually do, capturing their behavior as they interact with systems, execute commands, access files, and call APIs across development environments and production infrastructure. Observing agent activity directly on endpoints without requiring additional infrastructure such as proxies or gateways, it enables organizations to monitor real actions rather than just prompts or responses. It maps relationships between agents, tools, and connected services, offering a clear view of which agents are active, what permissions they use, and how they interact with internal and external resources.
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    Agno

    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.
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    InsForge

    InsForge

    InsForge

    InsForge is an AI-native backend platform designed specifically for agentic development, providing everything needed to build, manage, and deploy full-stack applications through AI coding agents. It functions as a Backend-as-a-Service with built-in primitives such as a managed PostgreSQL database, authentication with OAuth and JWT, cloud storage, serverless functions, real-time updates, and AI integrations, all accessible through a structured, agent-friendly interface. Unlike traditional backends built for human developers, InsForge exposes its services through a semantic layer and an MCP server that allows AI agents to understand, reason about, and operate backend infrastructure end to end. This enables agents to configure databases, manage schemas, handle authentication flows, deploy logic, and maintain applications with minimal manual intervention.
    Starting Price: $25 per month
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    KaibanJS

    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.
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    AgentScope

    AgentScope

    AgentScope

    AgentScope is an AI-driven agent observability and operations platform that provides visibility, control, and performance analytics for autonomous AI agents across production workloads. It enables engineering and DevOps teams to monitor, diagnose, and optimize complex multi-agent applications in real time by capturing detailed telemetry on agent actions, decisions, resource usage, and outcome quality. With rich dashboards and timelines, AgentScope helps teams trace execution flows, identify bottlenecks, and understand how agents interact with external systems, APIs, and data sources, improving debugging and reliability for autonomous workflows. It supports customizable alerting, log aggregation, and structured event views so teams can quickly surface anomalous behavior or errors across distributed agent fleets. In addition to real-time monitoring, AgentScope provides historical analysis and reporting that help teams measure performance trends, model drift, etc.
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    Naptha

    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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    Agora-1

    Agora-1

    Odyssey

    Agora-1 is a multi-agent world model that enables multiple participants, human or AI, to share and interact within the same world simulation in real time. It is the first in a series of multi-agent world models exploring how world models can enable new shared experiences across gaming, robotics, defense, education, foundation models, and more. World models generate high-fidelity simulations of arbitrary environments, but until now, they have largely been limited to a single active participant inside those simulated worlds. Agora-1 introduces multi-agent world simulations by allowing up to four players to interact in the same generated world at once. Players are matched into a shared deathmatch simulation, where every participant interacts with the same world simultaneously while the model simulates player actions, maintains shared world state, and streams generated pixels to each player.
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    OpenText Aviator Studio
    OpenText Aviator Studio is a no-code and pro-code platform for building, governing, connecting, deploying, and iterating enterprise AI agents. Designed for scale, security, and intelligent automation, it acts as an AI control plane for creating trusted agents across OpenText products and enterprise environments. Teams can rapidly design, test, and refine agents, develop multi-step workflows, chain reasoning, and deploy to different environments. Multi-agent choreography allows organizations to coordinate agents and systems across complex workflows, while a prompt library, reusable micro-capabilities, and standardized interfaces support consistent development and reuse. Aviator Studio includes enterprise-grade governance, permissions, policy enforcement, identity management, audit logging, data isolation, and guardrail settings to help prevent prompt injection and protect sensitive information.
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    VibeAgent

    VibeAgent

    Global Agent Studio

    VibeAgent is a cloud-based visual builder for creating and deploying AI agents and automated workflows. Developers, founders, and teams can map workflows on a drag-and-drop canvas, configure agent roles and model settings, and connect triggers, decision logic, tools, and knowledge sources. Workflows can start from schedules, webhooks, form submissions, chat, or other events, then coordinate multi-step actions across connected services. The platform supports models including GPT-4, Claude, Gemini, and open-source models, and can use document-based knowledge sources. Users can deploy agents and monitor performance through analytics dashboards. VibeAgent is intended for teams that want to prototype and operate tool-using agents without building the workflow infrastructure from scratch; available connectors, model access, execution limits, and other features may vary by plan.
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    OpenServ

    OpenServ

    OpenServ

    OpenServ is an applied AI research lab building the infrastructure for autonomous agents. Our next-generation multi-agent orchestration platform combines proprietary AI frameworks and protocols with supreme user simplicity. Automate complex tasks across Web3, DeFAI, and Web2. We’re accelerating the agentic field through numerous academic partnerships, in-house research, and community-focused research initiatives. See the whitepaper detailing the architecture of OpenServ. Seamless developer experience and agent development with our SDK. Receive early access to our platform, white-glove support, and an opportunity to shape the future.
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    FastAgency

    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.