Alternatives to Reflexio

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

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    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.
    5.0 out of 5 stars 3 Ratings for BAND
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    Overmind

    Overmind

    Overmind

    Overmind is a model training and deployment platform for teams building AI agents. It ingests production traces through OpenTelemetry and creates datasets from trace data, file uploads, and connectors for Langfuse, LangSmith, Braintrust, and Galileo. Teams can inspect agent context and runtime behavior, prepare and score datasets, evaluate prompts and models against their own examples, and optimize agent behavior through scored changes. The platform supports LoRA and full fine-tuning of open-weight models, benchmarking with configured evaluators, and deployment through an OpenAI-compatible endpoint; trained weights can also be downloaded. Users can work in the hosted console or run the platform on their own infrastructure with Docker Compose. It is designed for AI engineering and product teams operating agents in production that want to test, improve, or specialize models using their own data.
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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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    Molted

    Molted

    Molted.net

    Molted is a managed operating environment for autonomous AI agents. It lets teams deploy, host, monitor, recover, and scale OpenClaw-based agents without building their own cloud, DevOps, integration, and recovery stack. Molted provides agent-ready runtimes with persistent workspaces, browser automation, 1,000+ app integrations, dedicated email and voice per agent, monitoring, automatic recovery, and lifecycle management. Agents can use tools, access websites without APIs, communicate through email/voice/SMS, and keep working continuously. It is built for AI agencies, SaaS builders, OpenClaw consultants, and teams running agent fleets for customer-facing or internal workflows. Molted supports multi-agent management, versioned filesystems, restore points, REST API control, and cloud, on-premise, or sovereign deployments. Molted is not generic hosting; it is the run layer for production AI agents.
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    evalship

    evalship

    Garm Tech B.V.

    evalship helps engineering teams test and improve LLM-powered software. At setup, your coding agent reviews every scorer, judge and prompt in your evals and finds their flaws, such as a judge that scores 1.0 when its call fails, each with fix instructions. On every pull request, evalship compares results with the default branch, reports the evals a change really broke and the likely cause, sets flaky evals aside, and flags AI calls no eval exercises. Its check can block a merge that breaks an eval. Optimize has your coding agent try prompt and model changes on your machine, such as a cheaper model or clearer instructions, and evalship says which win beyond chance and by how much in pass rate, cost and time. Evals run with your own keys, in your own GitHub Actions or on your machine. evalship reads results from pytest, Vitest, Jest, promptfoo, Langfuse, Braintrust and LangSmith, with no SDK to add. Public repositories are free; paid plans start at $19 a month.
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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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    octomind
    octomind is an open-source runtime for building and running AI agents from a local command-line environment. It includes an agent engine, connections to major language-model providers, configurable skills and tools, and a runtime server for clients that interact with agents. Developers can use it for coding, research, workflow automation, and other tool-using tasks, with support for Windows, macOS, and Linux. The runtime supports more than 20 model providers, Model Context Protocol (MCP) tools, and event-driven workflows that respond to activity from services such as GitHub, Slack, and PagerDuty. octomind is distributed under the Apache 2.0 license; model-provider accounts or API usage may incur separate charges.
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    dcode

    dcode

    LangChain

    dcode is an open-source terminal coding agent for developers and software teams. Built on the Deep Agents SDK, it can plan and execute coding tasks, inspect and edit project files, run tools, and delegate work to subagents. Its interactive terminal interface streams responses and lets users resume conversations across sessions; headless mode supports scripted and CI workflows. Users select a compatible model provider and supply their own credentials, then customize models, tools, plugins, skills, memory, middleware, hooks, and approval rules. Tool calls can be approved or rejected, and code can run locally or in supported remote sandboxes. dcode supports MCP tools and can connect to LangSmith for tracing prompts, responses, tool calls, errors, and token usage. It is intended for developers who want to configure and inspect an AI coding agent rather than use a fixed coding assistant.
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    OneClickClaw

    OneClickClaw

    Bassline Botanica

    OneClickClaw is a managed hosting service for OpenClaw and Hermes Agent. It provisions a dedicated, single-tenant virtual server, installs and configures the agent, and handles HTTPS, monitoring, updates, and backups. Users supply an AI provider API key or supported subscription account and connect the agent to channels including Telegram, WhatsApp, Discord, Slack, and browser-based chat. A web dashboard provides server controls, provider and channel settings, monitoring, and subscription management. Servers are hosted in Denmark, with optional SSH access. The service is designed for individuals, freelancers, and technical users who want persistent AI agents without managing server setup and maintenance. AI model usage is billed separately by the selected provider; plans include a seven-day trial on a dedicated server.
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    LangSmith

    LangSmith

    LangChain

    Unexpected results happen all the time. With full visibility into the entire chain sequence of calls, you can spot the source of errors and surprises in real time with surgical precision. Software engineering relies on unit testing to build performant, production-ready applications. LangSmith provides that same functionality for LLM applications. Spin up test datasets, run your applications over them, and inspect results without having to leave LangSmith. LangSmith enables mission-critical observability with only a few lines of code. LangSmith is designed to help developers harness the power–and wrangle the complexity–of LLMs. We’re not only building tools. We’re establishing best practices you can rely on. Build and deploy LLM applications with confidence. Application-level usage stats. Feedback collection. Filter traces, cost and performance measurement. Dataset curation, compare chain performance, AI-assisted evaluation, and embrace best practices.
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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.
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    runx

    runx

    0state

    runx is an open-source runtime and command-line tool for creating, discovering, and executing governed skills for AI agents. Developers can define bounded workflows, grant specific credentials and permissions, and run skills locally with their own provider accounts. Runs can pause for approval or missing input, then resume while retaining a signed receipt that can be inspected and verified. Skills can be installed from a public registry and used with compatible agents such as Claude Code, Cursor, and Codex. An optional hosted service adds managed OAuth connections, scoped grants, API-based run submission and inspection, approval handling, and receipt notarization. The CLI can also operate locally or in a self-hosted environment. runx is intended for developers and platform teams building and operating AI-agent workflows that need explicit authority boundaries and auditable execution.
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    Dograh

    Dograh

    Dograh

    Dograh is an open source, self-hostable voice agent platform with a no-code workflow builder for creating production voice agents. Teams can choose their own inbound channels, speech-to-text, LLM, text-to-speech, and telephony providers, or replace the traditional cascade with speech-to-speech models for direct audio-in, audio-out conversations with natural turn-taking, interruption handling, and low latency. The platform supports inbound and outbound calling, widgets, telephony integrations, observability, traces, real-time analytics, hybrid pre-recorded voice plus TTS, and more than 70 languages. Its MCP server lets Claude Code, Cursor, OpenClaw, Codex, and other agent runtimes create, modify, and deploy voice agents directly from development environments. Dograh can run on your own servers, inside a private cloud or VPC, or in a managed environment, with support for models hosted entirely within your perimeter.
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    PrimeClaws

    PrimeClaws

    PrimeClaws.com

    PrimeClaws is a managed hosting platform for OpenClaw autonomous AI agents that lets users deploy and run their OpenClaw instances in the cloud with minimal setup and no DevOps knowledge; it focuses on providing a simple, one-click deployment process so an AI assistant built on OpenClaw can run 24/7 without requiring your laptop or local server to stay on. With support for major LLMs (like Claude, GPT, and Gemini) and persistent memory across sessions, agents can continue working and remembering context over time, and it integrates with messaging channels such as WhatsApp, Telegram, Slack, and others, so your AI assistant can be accessed and interacted with through familiar communication apps. Hosting through ClawHost abstracts infrastructure management, offering global cloud operations with persistent uptime, root access on self-hosted VPS environments, and full control over your agent’s environment, while automatically keeping the AI instance running.
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    Prefactor

    Prefactor

    Prefactor

    Prefactor is a real-time evaluation, observability, and reliability platform for production AI agents. It scores every run the moment it happens for quality, drift, cost, and data risk, then wires those evaluations into action so a failing agent is caught live instead of only appearing on a dashboard afterward. Teams can observe every model call, tool invocation, and decision as structured traces and spans, run LLM-as-judge, technical, qualitative, and custom evaluations on each step, and attach context from GitHub, Linear, Jira, databases, internal APIs, or other sources as ground truth. When a run crosses a defined threshold, Prefactor can block or throttle it, pause a sensitive action, or route it to a person for approval, modification, or rejection before execution, with every decision logged. The CLI discovers agents without a platform migration, while TypeScript and Python SDKs provide native support for LangChain, Claude, Vercel AI, OpenClaw, and LiveKit.
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    OpenComputer

    OpenComputer

    OpenComputer

    OpenComputer is a managed cloud runtime for building and deploying TypeScript AI agents. Developers define agent behavior, select models and tools, and deploy agents with durable sessions, streaming, schedules, memory and versioned environments. APIs and service connections let teams use agents in applications and workflows such as coding assistance and background automation.
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    Rapid Claw

    Rapid Claw

    Rapid Claw

    Rapid Claw is a managed cloud hosting platform for OpenClaw that enables users to deploy and run a fully autonomous AI agent in minutes without handling infrastructure, configuration, or DevOps tasks. It provides a dedicated, private OpenClaw instance that operates continuously in the cloud, allowing the agent to perform real work such as managing emails, automating workflows, reviewing code, processing data, and interacting with applications without human intervention. It removes the complexity of self-hosting, which typically requires server provisioning, dependency installation, environment configuration, and ongoing maintenance, by automating setup, updates, security, and backups. Users can launch an AI assistant with no coding, no API keys, and no terminal commands, then immediately begin interacting with it through a simple interface.
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    Langfuse

    Langfuse

    Langfuse

    Langfuse is an open source LLM engineering platform to help teams collaboratively debug, analyze and iterate on their LLM Applications. Observability: Instrument your app and start ingesting traces to Langfuse Langfuse UI: Inspect and debug complex logs and user sessions Prompts: Manage, version and deploy prompts from within Langfuse Analytics: Track metrics (LLM cost, latency, quality) and gain insights from dashboards & data exports Evals: Collect and calculate scores for your LLM completions Experiments: Track and test app behavior before deploying a new version Why Langfuse? - Open source - Model and framework agnostic - Built for production - Incrementally adoptable - start with a single LLM call or integration, then expand to full tracing of complex chains/agents - Use GET API to build downstream use cases and export data
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    Sandbox0

    Sandbox0

    Sandbox0

    Sandbox0 is an Apache-2.0 sandbox runtime for long-running AI agents and services that execute untrusted code. It provides isolated Linux environments with command execution, stateful contexts, file operations, SSH, supervised sessions, and network controls. Sandboxes retain a durable writable RootFS across successful pause-and-resume checkpoints; snapshots, restore, and forks support reusable workspaces. The Python, JavaScript/TypeScript, and Go SDKs, HTTP API, and s0 CLI let applications create and manage sandboxes. Sandbox0 Cloud provides hosted access, while teams can self-host the runtime on dedicated Nomad infrastructure. Default pause preserves filesystem state, not live process memory or external connections; experimental memory recovery requires compatible deployment support.
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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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    Agent Compute Engine
    Agent Compute Engine is a managed Google Cloud compute service that provides execution environments for AI agents. Each agent receives a hardware-isolated microVM with its own guest kernel and root-level control. The service supports rapid startup, pausing, checkpointing, snapshots, and resume workflows. Persistent workspaces retain agent files and context across sessions, while copy-on-write memory sharing supports parallel environments from common images. Agents can run code, shell commands, and browser actions in isolated sandboxes, with governed access to enterprise data through Google Cloud networking and identity controls. Developers can configure environment images, identity, network access, and lifecycle while Google manages the underlying compute fleet. The platform is designed for interactive assistants, coding agents, browser-based tasks, and large-scale evaluation and reinforcement-learning workloads.
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    Agent Substrate
    Agent Substrate is an open-source runtime for operating isolated, stateful agent and code-execution sandboxes on Kubernetes. It coordinates actor and worker lifecycles, places active workloads on a shared pool of ready capacity, and can suspend idle environments while preserving memory and filesystem state for later resumption. Sandboxes use gVisor or Cloud Hypervisor microVM isolation, with per-actor identity and network controls. Agent Substrate is designed for platform and infrastructure teams building agent-hosting services, coding environments, and other workloads that execute untrusted or intermittent tasks. The core project is Kubernetes-portable; Google Cloud also provides GKE-optimized deployment tooling. Optional Filestore agent volumes can persist workspaces across suspend and resume cycles.
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    KERNEL

    KERNEL

    Kernel

    KERNEL is a cloud browser infrastructure platform for developers building AI agents and browser-based automation. It provides managed browser sessions that agents can use to navigate websites, interact with page content, and perform tasks through code rather than relying on a local browser setup. The service is designed for production workloads, with persistent browser profiles, live browser viewing, session recording and replay, and controls for managing browser access. Teams can connect agent workflows through KERNEL's APIs, SDKs, and hosted MCP server, and use the platform for web research, data gathering, and other tasks that require interacting with websites. Plans for individual developers, startups, and enterprise teams include different browser concurrency, usage credits, and access to capabilities such as managed authentication, stealth mode, and regional browsers.
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    Archestra

    Archestra

    Archestra

    Archestra is an open source, self-hosted AI platform for deploying and governing agents across an organization. It provides agentic chat for non-developers, apps and skills, shared projects, a server-side agent runtime, MCP orchestration, permission-aware RAG, LLM and MCP proxies, security guardrails, and observability in one platform. Users sign in with SSO, and every tool call runs under that person’s own identity rather than a shared service account. Projects keep chats, files, scheduled tasks, and instructions together, while agents run in sandboxed containers and can start from schedules, emails, or webhooks. MCP servers run in the organization’s own Kubernetes environment and move through security-reviewed promotion flows with separate credentials and network policies. Knowledge bases can connect Confluence, Jira, drives, and internal documents while preserving source-system ACLs, so users only retrieve content they are already allowed to access.
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    Daytona

    Daytona

    Daytona

    Daytona is a cloud-native development runtime that enables developers and AI agents to instantly create, run, and manage isolated sandboxes for any codebase. Each sandbox runs inside a secure microVM with full Linux compatibility, networking, and persistent storage. Daytona provides SDKs in Python and TypeScript, allowing applications to programmatically execute code, run processes, upload files, or spin up environments dynamically. Teams use Daytona to replace complex local setups with reproducible cloud sandboxes that can be started in seconds and accessed through preview URLs, SSH, or APIs. It’s built for automation, observability, and scalability, powering everything from personal development environments to enterprise-grade agent runtimes.
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    OpenAI Agents API
    The Agents API lets developers build and run cloud agents with the same harness and infrastructure that powers Codex, fully managed by OpenAI. A production-ready agent can be created with a single API call by specifying the task, model, tools, and environment, while OpenAI hosts and maintains the agent harness. Developers can choose where agents run: in an OpenAI-hosted sandbox, on their own infrastructure, or through supported sandbox partners. OpenAI-hosted sandboxes provide secure environments where agents can run code, work with files, use packages, skills, and plugins, and produce artifacts. The API is designed for long-running work, with automatic context compaction that preserves relevant information as sessions span multiple context windows. Tool search loads relevant tool definitions only when needed, while programmatic tool calling lets agents run calls in parallel, chain related operations, and filter or combine results in code.
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    ClawSimple

    ClawSimple

    Localfirst LLC

    ClawSimple is a managed hosting service for OpenClaw, the open‑source personal AI agent. It lets you launch a dedicated OpenClaw bot in minutes without touching the terminal. ClawSimple automatically provisions a clean cloud server, runs the official installer, and keeps your agent online with 24/7 monitoring and an autonomous “Repair Agent” you can control via Telegram. You can start with built‑in AI credits or bring your own API keys for full model and cost control. Multiple agents can run on a single server, each with its own Telegram bot, identity, and model. ClawSimple focuses on secure, single‑tenant deployments, clear pricing, and a smooth setup flow so developers and non‑technical users can get a reliable OpenClaw bot running quickly and scale when needed.
    Starting Price: $4.92/month (billed yearly)
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    HostAiHub

    HostAiHub

    HostAiHub LTD

    HostAiHub is a managed hosting service for private instances of OpenClaw, Hermes, and n8n. Customers select an agent or workflow platform and deploy it in an isolated container with dedicated storage and an SSL-secured subdomain, without configuring servers themselves. A browser dashboard provides instance controls, while the service handles provisioning, updates, monitoring, and scheduled backups. Users can connect their own model-provider keys, with documented options including Anthropic, OpenAI, OpenRouter, DeepSeek, and Gemini; model usage is billed separately by the provider. HostAiHub also offers an OpenAI-compatible API service. Monthly, annual, and lifetime hosting plans are available, with prices varying by hosted platform and plan. The service is intended for founders, developers, agencies, and small teams that want to operate always-on AI agents or automated workflows without maintaining hosting infrastructure.
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    NoMac

    NoMac

    NoMac

    NoMac provides cloud macOS virtual machines on Apple silicon for iOS and macOS development. Sessions include macOS, Xcode, iOS simulator runtimes and common developer tools, enabling builds, tests and simulator work without a physical Mac. Developers and coding agents can control sessions through a browser desktop, CLI, SSH, HTTPS API or hosted Model Context Protocol (MCP) server. Workflows include building and testing apps, driving the simulator, capturing screenshots, signing apps and preparing TestFlight uploads. Each session is a fresh virtual machine deleted when stopped. An account drive can retain projects and build caches between sessions. NoMac serves iOS and macOS developers and teams using coding agents that need Xcode, including developers working from Windows or Linux. Usage is billed by the minute from prepaid credit, with a one-minute minimum and per-session spending cap.
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    Domino Enterprise AI Platform
    Domino is an enterprise AI platform designed to help organizations build, deploy, and scale AI systems that deliver real business outcomes. It provides end-to-end support for the AI lifecycle, from data science experimentation to production deployment and governance. The platform enables teams to access data, tools, and compute resources through a self-service environment with built-in IT controls. Domino supports the development of machine learning models, generative AI applications, and AI agents using preferred tools and frameworks. It also includes governance features such as model tracking, audit trails, and policy enforcement to ensure compliance and transparency. With hybrid and multi-cloud capabilities, organizations can run AI workloads across on-premises and cloud environments. Overall, Domino helps enterprises operationalize AI at scale while maintaining control, security, and efficiency.
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    Scalebrowser

    Scalebrowser

    Scalebrowser

    Scalebrowser is self-hosted browser infrastructure for AI agents that need to finish real work. Each isolated profile keeps the same identity, cookies, passkeys, memory, and tasks across restarts and machines. A patched Chromium engine, real local GPU values, human-like input, captcha handling, email and SMS codes, TOTP, and browser-level prompt control help agents get through the places where ordinary automation stops. Connect over MCP, REST, Node.js, Python, or direct CDP.
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    ApiGo

    ApiGo

    ApiGo

    ApiGo is a hosted AI model gateway for developers and teams building applications with language models. It provides a unified API endpoint for sending requests to supported model providers, with OpenAI-compatible request formats and model selection through a shared interface. The service includes model routing and fallback configuration, API key management, request and usage logs, per-model token pricing, workspace balance controls, and dashboards for reviewing consumption. Developers can use documented setup guides to connect coding assistants and agent tools such as Cursor, Claude Code, Codex CLI, OpenCode, Kimi Code, and OpenClaw. ApiGo is intended for teams that want to manage model-provider access, usage, and billing through one hosted gateway rather than configure each provider separately.
    Starting Price: $0.10/1M input tokens
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    EasyClaw

    EasyClaw

    EasyClaw

    EasyClaw is a desktop application that simplifies installing and running the OpenClaw autonomous AI agent stack locally without requiring DevOps, Python, Docker, or configuration work, offering a one-click setup and a graphical dashboard that gets your agent operating across popular messaging platforms rapidly. Once installed, EasyClaw manages the OpenClaw runtime and connects your AI agent (such as ClawdBot and MoltBot) to chat apps like WhatsApp, Telegram, Signal, and iMessage so you can interact with your assistant via natural language through familiar channels. It runs natively on your computer with all execution happening locally to preserve privacy and data security, letting the agent automate tasks ranging from inbox orchestration and document summarization to reminders, real-time translation, price comparisons, and other custom workflows without cloud dependencies.
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    Agent Teams

    Agent Teams

    MB Skydis

    Agent Teams is a hosted AI-agent workspace for solo founders and early-stage startups. Users can create a lead agent and specialist agents for product, growth, and operations, then coordinate work through shared tasks, files, and messages. Hosted agents can use persistent files and memory, browser access, tools, and schedules to handle ongoing work beyond a single browser session. The shared workspace lets users review agent conversations and activity and collaborate with invited colleagues. Agent Teams supports Hermes and OpenClaw workers, model and tool choices, and connectors for WhatsApp, Telegram, and Slack. Compatible AI clients, including Codex, Cursor, and Claude Code, can connect through supported reporting or MCP tools. The service is designed for startup teams coordinating AI-assisted product, growth, and operational work.
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    HyperLake

    HyperLake

    CerebrixOS

    HyperLake is built for organizations preparing for a world where AI agents become primary users of infrastructure. Today, most enterprise infrastructure was designed for humans, dashboards, applications, and scheduled pipelines. AI agents behave differently. They query data, call tools, trigger workflows, generate artifacts, operate across systems, and need continuous access to governed compute, data, policies, and services. HyperLake provides the command center to deploy, manage, run, secure, and govern that agentic infrastructure. The first product wedge is Agentic Data Cloud Infrastructure: open-stack data, analytics, semantic, workflow, and agent infrastructure deployed inside the customer’s own VPC, private cloud, or on-prem environment.
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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.
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    Braintrust

    Braintrust

    Braintrust Data

    Braintrust is an AI observability and evaluation platform designed to help teams build, monitor, and improve AI systems in production. It enables users to capture and inspect real-time traces of AI interactions, including prompts, responses, and tool usage. The platform allows teams to measure performance using automated and human evaluations to ensure output quality. Braintrust helps identify issues such as hallucinations, regressions, and performance drops before they impact users. It supports prompt and model comparisons, making it easier to optimize AI workflows over time. With scalable trace ingestion and real-time monitoring, teams gain full visibility into how their AI systems behave. The platform integrates with multiple programming languages and tools, allowing developers to work within their existing tech stack. Overall, Braintrust provides a comprehensive solution for maintaining and improving AI quality at scale.
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    StateFabric

    StateFabric

    J Gregory Technology Ltd.

    StateFabric a small infrastructure layer for AI agents that need more context than chat history. Once an agent starts using tools, running for longer sessions between restarts, ‘keep the messages in memory’ doesn’t really cut it. You need to know: - what happened? - what state changed? - which tools were called? - what context should go into the next model turn? StateFabric stores an append-only event log for agent runs, then derives working context from it. Today it supports: - Durable sessions and event storage - User/model/tool event timelines - Reconstructed session state from stored events - Compacted model-facing context - A dashboard for inspecting sessions, raw payloads, compaction artefacts, and usage - Google ADK integration via @statefabric/adk - Direct Node/REST usage via @statefabric/client (for custom runtimes)
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    NVIDIA NIM
    Explore the latest optimized AI models, connect AI agents to data with NVIDIA NeMo, and deploy anywhere with NVIDIA NIM microservices. NVIDIA NIM is a set of easy-to-use inference microservices that facilitate the deployment of foundation models across any cloud or data center, ensuring data security and streamlined AI integration. Additionally, NVIDIA AI provides access to the Deep Learning Institute (DLI), offering technical training to gain in-demand skills, hands-on experience, and expert knowledge in AI, data science, and accelerated computing. AI models generate responses and outputs based on complex algorithms and machine learning techniques, and those responses or outputs may be inaccurate, harmful, biased, or indecent. By testing this model, you assume the risk of any harm caused by any response or output of the model. Please do not upload any confidential information or personal data unless expressly permitted. Your use is logged for security purposes.
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    Cotlet

    Cotlet

    Take Group sp. z o.o.

    Cotlet is a hosted MCP server and REST API that lets AI agents work with web apps that lack a usable API. Users connect an app and sign in through a personal Chrome browser hosted in the cloud; agents can then call supported read and write actions through MCP, while scripts and backends can use the REST API. Its integration catalog covers tasks such as bookings, travel, customer support, invoicing, and marketing. Cotlet is aimed at developers and teams building agent workflows, as well as automation providers working with clients’ apps. It supports MCP clients including Claude, ChatGPT, Cursor, GitHub Copilot, Gemini, Windsurf, and n8n. Connected apps use the account holder’s signed-in session; Cotlet says it does not store passwords and encrypts browser profiles. Successful calls consume credits, while errors and timeouts do not. The company says integrations are regularly tested and updated when connected apps change.
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    Contextually

    Contextually

    Contextually

    Contextually is an enterprise AI platform designed to help organizations build and deploy production-ready AI agents that can reason over complex, domain-specific data using advanced context engineering. It provides a unified context layer that connects AI models to large volumes of enterprise knowledge, including documents, databases, and multimodal data, enabling agents to deliver accurate, grounded, and relevant outputs. It allows users to define and configure agents quickly through prebuilt templates, natural language prompts, or a visual drag-and-drop interface, supporting both dynamic agents and structured workflows tailored to specific use cases. It includes tools for ingesting and processing massive datasets from multiple sources, transforming unstructured and structured information into retrievable knowledge with intelligent parsing, metadata generation, and continuous updates.
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    Solid

    Solid

    Codapt lnc

    Solid is the operating system for always-on AI agents. This AI agent infrastructure runs agent software, allocates resources, connects agents to external systems, and applies shared controls. It provides a persistent runtime, memory, approved computers, identities, accounts, credentials, phone numbers, system access, and controlled spending so work can continue after a chat closes. Agents can use APIs, MCP, code, browsers, desktops, phones, and software interfaces, subject to customer permissions and system policies. Solid can build and test a missing integration, app, API, dashboard, or report needed to finish the job. Customer-set budgets and approvals govern provisioning and purchases. Solid provides agent orchestration plus visibility into available activity, code, resource state, costs, logs, and exceptions, with policies routing sensitive, unclear, or out-of-policy decisions to people. Builders can embed a Solid-powered agent through its API.
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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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    Macswarm

    Macswarm

    Macswarm

    Macswarm provides hosted macOS Pods on dedicated Apple silicon for Claude Code and Codex. Each Pod includes the latest Xcode, iOS runtimes, pre-booted Simulators, and XcodeBuildMCP, enabling coding agents to build iOS apps, run tests, and capture screenshots. Two to three active agents share a Pod in separate git worktrees, with a two-slot xcodebuild queue. Pods are cloned fresh and destroyed after use, with outbound-only networking and no inbound SSH. Usage is billed per Pod-hour and metered per second; idle Pods stop after ten minutes. EU (Netherlands) and US regions are available. The free plan includes 3 Pod-hours once. Pro is $99/month for 300 Pod-hours, and Team is $399/month for 1,500 Pod-hours. Early-access accounts are onboarded in signup order.
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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.
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    SenseLab

    SenseLab

    SenseLab

    SenseLab is a cloud-based memory and learning layer for AI agents and agent-driven applications. It provides shared knowledge spaces (“Rooms”) where agents and teams can record, retrieve, and share context across sessions, models, and tools. Agents can store findings, decision context, and outcomes; the service maintains versioned records and uses outcome feedback to adjust confidence in knowledge. SenseLab provides an MCP server and Python and TypeScript SDKs for connecting agent clients and applications through API-key access. Teams can use it to carry context between agents, coordinate work, review decision histories, and retain structured traces for evaluation or model-training workflows. It is intended for developers and organizations building systems with multiple AI agents. The vendor also documents a self-hosting option through its open-source codebase.
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    OpsAgents CLI Gateway
    OpsAgents CLI Gateway gives your AI agents every CLI they need behind one authenticated gateway. Run gcloud, gh, Firebase, Shopify, Trello and more - plus typed JSON routes - through a single remote cloud gateway, with no local installs. Each call is authenticated, scoped and logged: the agent posts the CLI and its arguments, the gateway runs it remotely and returns structured output, and every command is recorded to an audit trail. It is the platform layer under the OpsAgents agent fleet. Plans: Starter $29, Pro $99, Scale $299 per month. By OpsAgents AI.
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    KiloClaw

    KiloClaw

    Kilo Code

    KiloClaw is a fully managed, cloud-hosted version of the open source AI agent OpenClaw, designed to let users deploy and run a powerful autonomous AI assistant without handling infrastructure, setup, or maintenance. It provides a one-click deployment experience where users can launch a working AI agent in under 60 seconds, eliminating the need for Docker, servers, SSH configuration, or manual environment setup. It runs on Kilo’s infrastructure and connects to more than 500 AI models through the Kilo Gateway, allowing users to switch between models or bring their own API keys while maintaining a unified system for billing and management. KiloClaw agents are capable of performing real actions rather than just generating text, including browsing the web, running commands, managing files, scheduling tasks, and interacting across chat platforms such as Telegram, Discord, and Slack.
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    JDoodleClaw

    JDoodleClaw

    JDoodleClaw

    JDoodleClaw is a managed infrastructure platform that provides users with a private virtual machine pre-configured with OpenClaw, enabling them to run autonomous AI agents without handling setup, deployment, or DevOps tasks. It automatically provisions an isolated environment with dedicated compute resources, where OpenClaw is already installed and ready to use, allowing users to start building and running agents within minutes. It follows a bring-your-own API key model, giving users full control over which AI providers and credentials are used, while keeping all processing within their own private infrastructure. It eliminates the complexity of self-hosting, which typically involves configuring servers, installing dependencies, and maintaining environments, by handling provisioning, updates, and backups automatically. Each instance runs independently rather than in shared containers, improving data isolation, control, and performance consistency.
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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