Alternatives to Crewship

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

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    Gemini platform
    Gemini platform is an enterprise AI development and machine learning platform from Google Cloud that enables organizations to build, customize, deploy, and manage AI agents and intelligent applications. Formerly known as Vertex AI, the platform provides access to more than 200 foundation models from Google, third-party providers, and open-source communities. Its Agent Studio and Agent Development Kit allow developers to create autonomous agents, design multistep workflows, and integrate artificial intelligence with enterprise data and external tools. The platform also supports custom model training, fine-tuning, machine learning pipelines, model evaluation, and scalable inference infrastructure. Enterprise capabilities include agent identity management, centralized governance, security policies, persistent memory, and monitoring tools for evaluating agent performance. Gemini platform integrates with BigQuery, Google Antigravity, Google Cloud infrastructure, and developer frameworks to support generative AI applications, predictive analytics, and automated business workflows.
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    Anaconda

    Anaconda

    Anaconda

    Anaconda is an AI-native development platform that helps teams move from experimentation to production with trusted open-source packages, governed environments, and production-grade orchestration. The platform provides a secure foundation for Python, data science, machine learning, and AI development across the full model lifecycle. Anaconda Core helps teams manage complex Python dependencies with validated packages, automated security scanning, and intelligent conflict resolution. The Anaconda Platform supports governed AI development so organizations can reduce broken environments, stalled deployments, and unmanaged open-source risk. Its trusted distribution is used by millions of users, developers, contributors, organizations, and Fortune 500 companies. Built for enterprise AI teams, Anaconda helps organizations accelerate open-source AI innovation while maintaining control, security, and governance.
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    4.4 out of 5 stars 626 Ratings for Anaconda
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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.
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    Netra

    Netra

    Netra

    AI agents fail silently in production. Wrong answers, broken loops, cost spikes, behavior drift after a prompt change, and no stack trace to explain why. Netra is the single platform to trace, evaluate, simulate and security test your agents. Built for text, voice, image and video agents. SOC2 Type II certified. GDPR and HIPAA compliant. US and EU data residency. Integrates with: LangChain, LangGraph, CrewAI, LlamaIndex, OpenAI, Anthropic, Gemini, AWS Bedrock, and 30+ more.
    5.0 out of 5 stars 1 Rating for Netra
    Starting Price: $39/month
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    LangGraph

    LangGraph

    LangChain

    Gain precision and control with LangGraph to build agents that reliably handle complex tasks. Build and scale agentic applications with LangGraph Platform. LangGraph's flexible framework supports diverse control flows – single agent, multi-agent, hierarchical, sequential – and robustly handles realistic, complex scenarios. Ensure reliability with easy-to-add moderation and quality loops that prevent agents from veering off course. Use LangGraph Platform to templatize your cognitive architecture so that tools, prompts, and models are easily configurable with LangGraph Platform Assistants. With built-in statefulness, LangGraph agents seamlessly collaborate with humans by writing drafts for review and awaiting approval before acting. Easily inspect the agent’s actions and "time-travel" to roll back and take a different action to correct course.
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    Vulnify

    Vulnify

    Vulnify

    Vulnify is runtime authorization for AI agents. Before a sensitive tool call runs, your code calls check() and gets ALLOW, REVIEW or BLOCK, with a 0-100 risk score and the reasons: action, data sensitivity, destination, volume. REVIEW pauses only that action until a person approves. Start in monitor mode, fail closed by default. Policies as code, Node and Python SDKs (MIT) with LangChain, MCP, CrewAI and LangGraph adapters, and a hash-chained audit log with JSON/CSV export. Free plan available.
    Starting Price: Free plan available
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    LangMem

    LangMem

    LangChain

    LangMem is a lightweight, flexible Python SDK from LangChain that equips AI agents with long-term memory capabilities, enabling them to extract, store, update, and retrieve meaningful information from past interactions to become smarter and more personalized over time. It supports three memory types and offers both hot-path tools for real-time memory management and background consolidation for efficient updates beyond active sessions. Through a storage-agnostic core API, LangMem integrates seamlessly with any backend and offers native compatibility with LangGraph’s long-term memory store, while also allowing type-safe memory consolidation using schemas defined in Pydantic. Developers can incorporate memory tools into agents using simple primitives to enable seamless memory creation, retrieval, and prompt optimization within conversational flows.
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    Flint AI

    Flint AI

    SandboxAQ

    Flint AI is a local-first, framework-agnostic AgentOps CLI that helps developers determine whether an AI agent is reliable before it reaches production. One command, flintai scan, analyzes Python source code for security vulnerabilities, misconfigurations, risky tool access, missing guardrails, and quality issues, then uses AI reasoning to triage likely false positives. A second command, flintai eval, sends functional and adversarial prompts to a running agent and scores its responses across more than 35 built-in evaluations, including factual accuracy, instruction adherence, prompt injection resistance, jailbreak resilience, and other runtime behaviors. Each agent receives a reliability score, with findings mapped to OWASP Agentic Security Initiative risks ASI01 through ASI10 and severity scored using CVSS v4.0. Flint AI works with agent frameworks and SDKs including Claude Agents SDK, LangChain, CrewAI, Anthropic SDK, OpenAI SDK, MCP servers, and AutoGen.
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    Traccia

    Traccia

    Algen AI

    Traccia is an OpenTelemetry-native observability, governance, and policy enforcement platform for production AI agents. It gives engineering teams complete visibility into every LLM call, tool invocation, decision, token, and dollar spent across frameworks like LangChain, CrewAI, OpenAI Agents SDK, AutoGen, and LlamaIndex. Beyond tracing, Traccia helps organizations govern AI systems with runtime policies that can detect and block unsafe behavior, runaway costs, restricted model usage, and PII exposure before incidents reach production. Accurate cost attribution, agent health monitoring, a unified agent registry, and EU AI Act evidence generation make it suitable for enterprise deployments. With a lightweight open-source SDK and managed platform, Traccia enables teams to build, debug, monitor, and govern AI agents at scale without vendor lock-in, using standard OpenTelemetry instrumentation.
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    LangChain

    LangChain

    LangChain

    LangChain is a powerful, composable framework designed for building, running, and managing applications powered by large language models (LLMs). It offers an array of tools for creating context-aware, reasoning applications, allowing businesses to leverage their own data and APIs to enhance functionality. LangChain’s suite includes LangGraph for orchestrating agent-driven workflows, and LangSmith for agent observability and performance management. Whether you're building prototypes or scaling full applications, LangChain offers the flexibility and tools needed to optimize the LLM lifecycle, with seamless integrations and fault-tolerant scalability.
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    OpenUI

    OpenUI

    Thesys

    OpenUI is an open-source (MIT) generative UI framework for AI agents. Instead of plain text, your agent writes OpenUI Lang, a compact, streaming-first language, and OpenUI renders it progressively as real UI: charts, tables, forms, cards and layouts. Rendering is safe by default: the model can only use components you register and no generated code is executed, so your design system stays in control. A framework-agnostic core powers first-party runtimes for React, Vue, Svelte and Angular, with ready-made chat interfaces and integrations for LangChain/LangGraph, the Vercel AI SDK, Mastra, Google ADK, assistant-ui, CopilotKit, AG-UI and A2UI. In its published benchmark, OpenUI Lang uses about half the tokens of equivalent JSON UI formats, so interfaces stream faster and cost less.
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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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    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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    Agency

    Agency

    Agency

    Agency helps enterprises build, evaluate, and monitor AI agents. From the team at AgentOps.ai. Agen.cy (Agency AI) develops cutting edge AI agents using CrewAI, AutoGen, CamelAI, LLamaIndex, Langchain, Cohere, MultiOn + many more.
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    Macyou

    Macyou

    Macyou LLC

    Macyou rents dedicated Apple Silicon Macs for AI workloads. Users configure a Mac (M4 Mac mini to Mac Studio M3 Ultra with 256 GB unified memory), pick a pre-configured stack — local LLMs via Ollama (Llama, Qwen, Mistral, DeepSeek), agent frameworks (CrewAI, LangGraph), or ML dev environments (MLX, Jupyter) — and get a running deployment in about 5 minutes. Every deployment exposes an OpenAI-compatible API, so existing OpenAI SDK code works by changing base_url; access also includes SSH with root and a browser-based remote desktop. Each customer gets a dedicated physical machine with full-disk encryption and a disk wipe between tenants, hosted in a GDPR-friendly jurisdiction. Pricing is a fixed monthly fee per machine with no per-token charges; Thunderbolt 5 clustering pools unified memory across nodes for larger models. Published, measured inference benchmarks (raw JSON, CC BY 4.0) show real tokens per second per chip.
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    Deep Agents

    Deep Agents

    LangChain

    Deep Agents is an open-source developer library and agent harness for building LLM-powered agents that can work through multi-step tasks. It provides an agent loop with built-in capabilities for planning, persistent memory, file-system interaction, and delegation to subagents, while allowing developers to connect model providers and tools. The library is intended for software developers and teams creating custom agent applications, including research, coding, and other workflows that require an agent to plan and act across several steps. Developers can extend its behavior with custom tools, middleware, and backends, and integrate it with LangGraph and LangSmith for orchestration, tracing, and deployment workflows. Deep Agents is a software development framework rather than a ready-made end-user agent application; users implement and run agents within their own applications and environments.
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    RA.Aid

    RA.Aid

    RA.Aid

    ​RA.Aid is an open source AI assistant that autonomously handles research, planning, and implementation to expedite software development processes. Built on LangGraph's agent-based task execution framework, RA.Aid operates through a three-stage architecture. RA.Aid supports multiple AI providers, including Anthropic's Claude, OpenAI, OpenRouter, and Gemini, allowing users to select models that best fit their requirements. It also features web research capabilities, enabling the agent to pull real-time information from the internet to enhance its understanding and execution of tasks. It offers an interactive chat mode, allowing users to guide the agent directly, ask questions, or redirect tasks as needed. Additionally, RA.Aid integrates with 'aider' via the '--use-aider' flag to leverage specialized code editing capabilities. It is designed with a human-in-the-loop interaction mode, enabling the agent to seek user input during task execution to ensure higher accuracy.
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    Atla

    Atla

    Atla

    Atla is the agent observability and evaluation platform that dives deeper to help you find and fix AI agent failures. It provides real‑time visibility into every thought, tool call, and interaction so you can trace each agent run, understand step‑level errors, and identify root causes of failures. Atla automatically surfaces recurring issues across thousands of traces, stops you from manually combing through logs, and delivers specific, actionable suggestions for improvement based on detected error patterns. You can experiment with models and prompts side by side to compare performance, implement recommended fixes, and measure how changes affect completion rates. Individual traces are summarized into clean, readable narratives for granular inspection, while aggregated patterns give you clarity on systemic problems rather than isolated bugs. Designed to integrate with tools you already use, OpenAI, LangChain, Autogen AI, Pydantic AI, and more.
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    Switch AI

    Switch AI

    Flint AI

    Switch is a collaborative workspace from Flint AI that enables humans and AI agents to work together through existing messaging platforms. The platform creates shared rooms where people, agents, decisions, files, and work history remain available as tasks move between different participants and agents. Teams can bring agents into Slack, Microsoft Teams, Discord, and Mattermost without replacing their existing communication workflows. Switch works with AI and agent technologies including Claude Code, Anthropic Claude, OpenAI, LangChain, LangGraph, Amazon Bedrock, Google Vertex AI, ADK, and custom-built agents. Multiple specialized agents can coordinate within the same room, use work completed by other agents, respond to human direction, and hand tasks to one another while retaining shared context. Switch is extensible by design and is intended to give organizations a common workspace for coordinating human-agent teams without requiring them to migrate to a new collaboration environment.
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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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    OneCommand Platform
    Every auto dealership is looking for an advantage. OneCommand is the successful dealer’s secret weapon for delivering consistent results in their sales and service departments. Join thousands of dealers who are using the OneCommand Platform and CRM every day. OneCommand is the industry leader in deploying leading-edge technology that is proven to increase responses, drive traffic and lower marketing costs. The only CRM that complements a dealership's internal processes and makes them better. Solutions designed to take your marketing to the next level. We are car people with an average of 15 years of experience in multiple segments of the auto industry. We know what is important to auto dealers and we know how to deliver it. Every day OneCommand sends over 1,000,000 communications on behalf of our clients. But, our success is not about volume, it is about helping dealers communicate with their most precious resource, customers and prospects.
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    Herdr

    Herdr

    Herdr

    Herdr is a terminal-based runtime and multiplexer for developers who run AI coding agents, shells, tests, and other command-line tools. It organizes work into workspaces, tabs, and panes managed by a background server, so processes can keep running when a client disconnects. Users can reattach locally or connect to Herdr on other machines over SSH. The software detects supported coding agents and displays whether they are working, blocked, idle, or done; integrations can preserve native agent sessions after a server restart. Its CLI and local socket API let scripts and agents inspect sessions, manage panes, start or prompt agents, and wait for state changes. Developers can configure keybindings and themes and extend workflows with local executable plugins. Herdr is installed on macOS, Linux, or Windows and is released under the Apache 2.0 license.
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    FirstHelm

    FirstHelm

    FirstHelm

    FirstHelm is a control plane for AI agents. It sits between your agent fleet — n8n, OpenAI, Anthropic, CrewAI, LangChain, Microsoft Copilot Studio, or any custom agent via REST API — and the rest of the world, deciding what each agent is allowed to do, not just showing what it did. Every action is logged and checked in flight against your rules: budget caps, blocked actions, and per-mission cost and token visibility. Expensive, risky or irreversible actions are held for human approval, and unanswered approvals expire safely — silence is not consent. Live dashboards let you steer agents mid-mission, and FirstHelm generates audit trails and compliance exports mapped to the EU AI Act, ISO 42001, SOC 2, UK GDPR, NIST AI RMF and FCA expectations — 38 controls, scored live from your own data. Freemium, framework-agnostic, UK-built.
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    Navarch

    Navarch

    SagentLab

    Navarch is the command layer for teams running AI coding agents. Crews plan, build, review, QA and ship real software across several repos at once, while you set priorities, budgets and approval gates. Every task lands on an append-only ledger with its pull request, before/after screenshots and an independent review attached, so you judge the work from evidence instead of re-reading diffs. Your repos stay in GitHub, your agents run on your machines or ours.
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    Agent Communication Protocol (ACP)
    The Agent Communication Protocol (ACP) is an open interoperability standard designed to enable seamless communication between AI agents, applications, and human users. It provides a standardized RESTful API that supports synchronous and asynchronous interactions, streaming communication, long-running tasks, and both stateful and stateless operations. ACP is framework-agnostic, allowing agents built with technologies such as BeeAI, LangChain, CrewAI, or custom solutions to work together without requiring changes to their internal architecture. The protocol supports all content modalities through MimeTypes, making it flexible enough to handle text, images, audio, video, and custom data formats. ACP also includes capabilities for online and offline agent discovery, helping organizations find and connect compatible agents across different environments.
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    Scalekit

    Scalekit

    Scalekit

    Scalekit is the MCP gateway for AI agents. It is for developers and platform teams who need an agent to call tools as the user, not through a shared service account. One endpoint reaches 600+ connectors and 35,000+ tools, including Salesforce, Gmail, Slack, Notion, HubSpot, Jira, and GitHub. Scalekit finds that user's credentials, checks permission, runs the call, and returns a clean response. Tokens stay in an AES-256 vault. It works with Anthropic, OpenAI, LangChain, Google ADK, Vercel AI, and Mastra. Run it in the Scalekit cloud (US, with EU residency available), in your VPC, or self-hosted. SOC 2 Type II and ISO 27001. A HIPAA BAA is available on Enterprise. The Free plan includes 10,000 tool calls and 10,000 trigger events a month. Growth is $99 a month for 100,000 tool calls. Enterprise pricing is custom.
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    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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    Pylar

    Pylar

    Pylar

    Pylar is a secure data-access layer that sits between AI agents and your databases, enabling agents to safely interact with structured data without giving them direct database access. It connects to one or more data sources (like BigQuery, Snowflake, PostgreSQL, business apps such as HubSpot or Google Sheets). Pylar can create governed SQL views using its built-in SQL IDE; those views define exactly which tables, columns, and rows agents are allowed to access. It lets you build “MCP tools” (either by writing natural-language prompts or manual configuration) that wrap SQL queries into standardized, safe operations. Agents can access data through a single MCP endpoint, compatible with multiple agent builders like custom AI assistants, no-code automation tools, or integrations (e.g. Zapier, n8n, LangGraph, VS Code, etc.).
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    Cosmos

    Cosmos

    Augment Code

    Cosmos by Augment Code is an AI agent orchestration platform designed to automate and coordinate software development workflows across engineering organizations. The platform enables teams to deploy specialized AI agents that handle tasks such as code generation, pull request reviews, vulnerability remediation, and incident investigation. Cosmos uses a Context Engine to provide agents with an understanding of codebases, dependencies, and existing development patterns. Its event-driven automation capabilities trigger workflows through repository activity, scheduled tasks, webhooks, and integrations with development tools. The platform supports shared organizational knowledge, isolated execution environments, and human approval checkpoints for managing automated operations. Cosmos integrates with GitHub, GitLab, Jira, Linear, Slack, and other engineering systems to connect AI agents with existing software delivery processes.
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    Acontext

    Acontext

    MemoDB

    Acontext is a context platform for AI agents. It stores multi-modal messages/artifacts, monitors agents' task status, and runs a Store → Observe → Learn → Act loop that identifies successful execution patterns, so autonomous agents can act smarter and succeed more over time. Developer Benefits: Less Tedious Work: Store multi-modal context and artifacts in one place by integrating all context data without configuring Postgres, S3, or Redis, and it only requires a few lines of code. Acontext handles repetitive, time-consuming configuration tasks, so developers don’t have to. Self-Evolving Agents: Similar to Claude Skills, which require predefined rules, Acontext allows agents to automatically learn from past interactions, reducing the need for constant manual updates and tuning. Easy Deployment: Open-source, one-command setup, One-line install. Ultimate Value: Improve agent success rates and reduce running steps, then save costs.
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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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    OpenAI Frontier
    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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    Oz

    Oz

    Warp

    Oz is a cloud-based orchestration platform for AI coding agents that lets developers and teams run, manage, automate, and scale unlimited parallel cloud coding agents without building custom infrastructure, providing programmable, auditable, and fully steerable workflows that automate repetitive development tasks and complex code changes. It enables you to launch agents from the CLI, web app, APIs, SDKs, Warp Terminal, or even mobile, orchestrate hundreds of agents in parallel with built-in audit trails, session tracking, and visibility, and monitor or interact with running agents in a shared control plane. Oz supports flexible hosting on your infrastructure or Warp’s, isolates each agent in secure environments, produces real artifacts like plans and pull requests, and handles multi-repo changes so agents can coordinate sweeping updates across large codebases.
    Starting Price: $18 per month
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    Teradata Enterprise AgentStack
    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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    ServiceNow AI Agents
    ServiceNow's AI Agents are autonomous systems embedded within the Now Platform, designed to perform repetitive tasks traditionally handled by humans. These agents interact with their environment to collect data, make decisions, and execute tasks, enhancing efficiency over time. Leveraging domain-specific large language models and a robust reasoning engine, they possess a deep understanding of business contexts, enabling continuous improvement in outcomes. Operating natively across workflows and data systems, AI Agents facilitate end-to-end automation, boosting team productivity by orchestrating workflows, integrations, and actions throughout the enterprise. Organizations can deploy prebuilt AI agents or develop custom agents tailored to specific needs, all functioning seamlessly on the Now Platform. This integration allows employees to focus on more strategic initiatives by automating routine tasks.
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    AI Autopilot

    AI Autopilot

    AI Autopilot

    AI Autopilot is an advanced agentic AI automation platform designed specifically for MSPs to streamline IT operations with intelligent automation. It provides specialized AI agents that handle ticket triage, prioritization, routing, escalation, and SLA monitoring with MSP-grade accuracy. The system integrates natively with major PSA, RMM, documentation, and automation tools like ConnectWise, Autotask, Ninja RMM, IT Glue, Liongard, and Rewst. By automating repetitive tasks, AI Autopilot helps MSPs resolve tickets faster, reduce labor costs, and deliver 24/7 support coverage. Users can even enable ticket creation directly from Microsoft Teams and Slack for a frictionless support experience. With upcoming integrations like MCP, CrewAI, LangChain, and deep RPA orchestration, the platform continues to evolve into a next-generation multi-agent AI infrastructure for MSPs.
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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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    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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    FPT AI Factory
    FPT AI Factory is a comprehensive, enterprise-grade AI development platform built on NVIDIA H100 and H200 superchips, offering a full-stack solution that spans the entire AI lifecycle, FPT AI Infrastructure delivers high-performance, scalable GPU resources for rapid model training; FPT AI Studio provides data hubs, AI notebooks, model pre‑training, fine‑tuning pipelines, and model hub for streamlined experimentation and development; FPT AI Inference offers production-ready model serving and “Model-as‑a‑Service” for real‑world applications with low latency and high throughput; and FPT AI Agents, a GenAI agent builder, enables the creation of adaptive, multilingual, multitasking conversational agents. Integrated with ready-to-deploy generative AI solutions and enterprise tools, FPT AI Factory empowers businesses to innovate quickly, deploy reliably, and scale AI workloads from proof-of-concept to operational systems.
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    Starkomand

    Starkomand

    Starkomand

    Starkomand puts your AI coding agents on a voice-controlled canvas for Mac. Run Claude Code, Codex, Cursor, and more with your existing AI subscriptions. Command agents to draw diagrams, open browser previews, and hand off work between models all on the same canvas.
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    Optimizely Opal
    Optimizely Opal platform embeds advanced artificial intelligence across its Digital Experience Platform to help teams create, optimize, and personalize digital experiences with less manual effort and more strategic impact; at its core is Optimizely Opal, an AI agent orchestration and assistance system that connects context from across Optimizely One and executes tasks in workflows rather than just returning text responses, enabling teams to plan campaigns, generate content, build experiment ideas, analyze results, and guide optimization decisions with branded, context-aware AI agents. The AI capability spans content management, personalization, experimentation, analytics, and audience segmentation: it can suggest and auto-create experiment variations and test plans, summarize results with actionable recommendations, generate tailored digital content and messaging, and guide personalization based on real-time customer behavior and preferences.
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    PydanticAI

    PydanticAI

    Pydantic

    PydanticAI is a Python-based agent framework designed to simplify the development of production-grade applications using generative AI. Built by the team behind Pydantic, the framework integrates seamlessly with popular AI models such as OpenAI, Anthropic, Gemini, and others. It offers type-safe design, real-time debugging, and performance monitoring through Pydantic Logfire. PydanticAI also provides structured responses by leveraging Pydantic to validate model outputs, ensuring consistency. The framework includes a dependency injection system to support iterative development and testing, as well as the ability to stream LLM outputs for rapid validation. It is ideal for AI-driven projects that require flexible and efficient agent composition using standard Python best practices. We built PydanticAI with one simple aim: to bring that FastAPI feeling to GenAI app development.
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    01.AI

    01.AI

    01.AI

    The 01.AI Super Employee platform transforms enterprise operations with AI agents capable of deep reasoning, task planning, and end-to-end execution. Through its centralized Solution Console, organizations can manage knowledge bases, train custom models, and deploy business-ready AI solutions with ease. Built for enterprise security, it supports on-premise deployment, secure sandboxing, and MCP connectivity for controlled access to legacy systems and external tools. 01.AI offers a comprehensive suite of industry-specific agents—from sales and insurance to supply chain, finance, and government—each designed to automate workflows across browsers, terminals, cloud phones, and interpreters. With native support for leading LLMs like DeepSeek, Qwen, and Yi, businesses gain a flexible and future-ready AI stack. The platform accelerates AI adoption by enabling rapid deployment, continuous evolution, and seamless integration across enterprise environments.
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    Microsoft Copilot Studio
    Microsoft Copilot Studio is a comprehensive platform that enables users to create and manage AI-driven agents tailored to specific business needs. Utilizing low-code and generative AI capabilities, it allows for the design of agents that can access internal knowledge bases, execute actions through a wide array of data connectors, and operate autonomously to enhance productivity. These agents can be seamlessly deployed across various channels, including Microsoft 365 applications, internal websites, and mobile apps, ensuring integration into existing workflows. Copilot Studio also offers robust governance features, providing IT departments with centralized control over usage, analytics, and security policies.
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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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    Intent

    Intent

    Augment Code

    Intent is a public beta desktop workspace designed for spec-driven development and multi-agent orchestration, enabling developers to plan, execute, and iterate on complex coding tasks using coordinated AI agents. It places living specifications at the center of the workflow so teams can define what should be built and allow agents to implement it while keeping the spec continuously updated to reflect actual output. It provides a unified environment where multiple agents can run in parallel without conflicts, eliminating the need to juggle terminals, branches, or scattered prompts. Powered by Augment’s Context Engine, each agent shares a deep understanding of the entire codebase, ensuring alignment between planning, execution, and verification stages. Intent supports major state-of-the-art models and allows developers to mix and match them based on task complexity, whether for architecture design, rapid iteration, or deep code analysis.
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    Agent2Agent (A2A)
    Agent2Agent (A2A) is a protocol developed by Google to enable seamless communication between AI agents. It facilitates the transfer of knowledge and tasks between different AI systems, allowing them to collaborate and execute complex workflows. A2A aims to enhance interoperability between AI agents, enabling more sophisticated, multi-agent systems that can perform tasks autonomously across various platforms and services.
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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.
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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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    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.