Alternatives to HyperLake

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

  • 1
    Google Cloud Platform
    Google Cloud is a cloud-based service that allows you to create anything from simple websites to complex applications for businesses of all sizes. New customers get $300 in free credits to run, test, and deploy workloads. All customers can use 25+ products for free, up to monthly usage limits. Use Google's core infrastructure, data analytics & machine learning. Secure and fully featured for all enterprises. Tap into big data to find answers faster and build better products. Grow from prototype to production to planet-scale, without having to think about capacity, reliability or performance. From virtual machines with proven price/performance advantages to a fully managed app development platform. Scalable, resilient, high performance object storage and databases for your applications. State-of-the-art software-defined networking products on Google’s private fiber network. Fully managed data warehousing, batch and stream processing, data exploration, Hadoop/Spark, and messaging.
    Leader badge
    Compare Google Cloud Platform vs. HyperLake View Software for Google Cloud Platform
    Visit Website for Google Cloud Platform
  • 2
    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.
    Leader badge
    Compare Gemini platform vs. HyperLake View Software for Gemini platform
    Visit Website for Gemini platform
  • 3
    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
    Compare BAND vs. HyperLake View Software for BAND
    Visit Website for BAND
  • 4
    Amazon Web Services (AWS)
    Amazon Web Services (AWS) is the world’s most comprehensive cloud platform, trusted by millions of customers across industries. From startups to global enterprises and government agencies, AWS provides on-demand solutions for compute, storage, networking, AI, analytics, and more. The platform empowers organizations to innovate faster, reduce costs, and scale globally with unmatched flexibility and reliability. With services like Amazon EC2 for compute, Amazon S3 for storage, SageMaker for AI/ML, and CloudFront for content delivery, AWS covers nearly every business and technical need. Its global infrastructure spans 120 availability zones across 38 regions, ensuring resilience, compliance, and security. Backed by the largest community of customers, partners, and developers, AWS continues to lead the cloud industry in innovation and operational expertise.
  • 5
    Vercel

    Vercel

    Vercel

    Vercel is an AI-powered cloud platform that helps developers build, deploy, and scale high-performance web experiences with speed and security. It provides a unified set of tools, templates, and infrastructure designed to streamline development workflows from idea to global deployment. With support for modern frameworks like Next.js, Svelte, Vite, and Nuxt, teams can ship fast, responsive applications without managing complex backend operations. Vercel’s AI Cloud includes an AI Gateway, SDKs, workflow automation tools, and fluid compute, enabling developers to integrate large language models and advanced AI features effortlessly. The platform emphasizes instant global distribution, enabling deployments to become available worldwide immediately after a git push. Backed by strong security and performance optimizations, Vercel helps companies deliver personalized, reliable digital experiences at massive scale.
  • 6
    Phinite

    Phinite

    Phinite AI

    Phinite provides shared infrastructure for building, deploying, and governing AI agents across orchestration, security, observability, lifecycle management, and environment promotion — so engineering teams don't rebuild these layers for every new agent use case. Core capabilities: Orchestration for multi-agent systems (agent-to-agent, nested calls) Deep session-level observability: execution timelines, decision variables, tool calls, latency/cost tracking Private Agent Registry for skill discoverability Eval suite for accuracy/safety benchmarking Dev-to-Production workflow with environment promotion Kubernetes-native deployment, VPC-internal deployability SOC 2 Type 2 compliance
  • 7
    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.
  • 8
    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.
  • 9
    TinyFish

    TinyFish

    TinyFish

    TinyFish is the web operating layer for AI agents, providing the infrastructure agents need to reliably access and operate across the live web. As AI applications evolve beyond text generation into autonomous systems that gather information, navigate websites, and complete multi-step tasks, fragmented automation stacks and custom-built infrastructure become difficult to maintain. TinyFish unifies web search, content extraction, browser infrastructure, and agentic web interaction within a single platform. Agents can search the live web, extract clean LLM-ready content from modern websites, render JavaScript-heavy pages, and execute authenticated workflows without stitching together multiple vendors or maintaining custom infrastructure. Built for production AI systems, TinyFish emphasizes accuracy, efficiency, freshness, and scalability. By providing clean web context and dependable execution across dynamic web environments, the platform helps developers build AI applications that
  • 10
    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.
  • 11
    Ausca

    Ausca

    Ausca

    Ausca provides on-demand infrastructure for AI agents and developers through a public service catalog and API. Offerings include document OCR and analysis, audio and video transcription, bounded remote browser sessions, and temporary receive-only email inboxes. Each service has defined inputs, limits, pricing, and instructions. Developers can connect through HTTP with x402 payment, MCP-compatible tools, command-line utilities, or typed clients. Discovery is available without an account or API key; paid execution requires explicit payment authorization. Services charge per invocation or lease, and completed work can return a verifiable receipt. Ausca is designed for developers and agent operators adding document, media, browser, or inbox functions to automated workflows without deploying those services themselves.
  • 12
    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.
  • 13
    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.
  • 14
    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.
  • 15
    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.
  • 16
    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.
  • 17
    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.
  • 18
    Mirantis OpenStack for Kubernetes
    Whether your workloads are restricted to on-prem data centers or you’re battling out-of-control public cloud costs, private cloud virtualization is a crucial piece of your infrastructure puzzle. Mirantis OpenStack for Kubernetes gives you the power of public cloud and the time-tested reliability of OpenStack—all built on a flexible and resilient foundation of Kubernetes, putting you back in control of your cloud. OpenStack is the leading open source private cloud infrastructure-as-a-service (IaaS) framework, providing a feature-rich, mature environment for hosting virtual machines, networks, and storage. Mirantis OpenStack for Kubernetes brings virtualized infrastructure into the cloud native world, providing an easy-to-use virtualization platform built on Kubernetes for optimal flexibility and resilience.
  • 19
    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.
  • 20
    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.
  • 21
    OpenServ

    OpenServ

    OpenServ

    OpenServ is an applied AI research lab building the infrastructure for autonomous agents. Our next-generation multi-agent orchestration platform combines proprietary AI frameworks and protocols with supreme user simplicity. Automate complex tasks across Web3, DeFAI, and Web2. We’re accelerating the agentic field through numerous academic partnerships, in-house research, and community-focused research initiatives. See the whitepaper detailing the architecture of OpenServ. Seamless developer experience and agent development with our SDK. Receive early access to our platform, white-glove support, and an opportunity to shape the future.
  • 22
    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.
  • 23
    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.
  • 24
    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.
  • 25
    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.
  • 26
    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.
  • 27
    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.
  • 28
    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)
  • 29
    CreateOS Sandbox
    CreateOS Sandbox is a hosted compute service for developers building AI agents, code-execution platforms, and developer tools. It creates isolated Firecracker micro-virtual machines, each with its own Linux kernel, where teams can run untrusted or model-generated code. Developers can provision environments through a TypeScript SDK, command-line interface, MCP tools, or REST API, execute commands, and connect sandboxes through private networks. Sandboxes can be paused and resumed with guest state preserved, configured from reusable templates, and connected to customer-owned Amazon S3, MinIO, or Cloudflare R2 storage. Usage is metered per second for compute, memory, and disk; paused environments continue to incur memory and storage charges. The service offers EU and US regions, plus an enterprise option to run on customer infrastructure.
  • 30
    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.
  • 31
    Fly.io

    Fly.io

    Fly.io

    Fly.io is a modern cloud platform designed to help developers deploy and run applications quickly and efficiently. It uses lightweight virtual machines called Fly Machines that start instantly and scale based on demand. The platform allows developers to run any code in secure, hardware-isolated environments without complex infrastructure setup. Fly.io supports global deployment across multiple regions, ensuring low-latency performance for users worldwide. It also includes built-in private networking, storage solutions, and monitoring tools. Developers can use their preferred frameworks and tools without needing extensive configuration. By simplifying cloud infrastructure, Fly.io enables teams to build, deploy, and scale applications with ease.
  • 32
    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.
  • 33
    Sprites

    Sprites

    Fly.io

    Sprites by Fly.io is a stateful sandbox platform for running arbitrary code in hardware-isolated Linux environments. A Sprite acts like a persistent Linux computer where developers can execute AI agents, user-uploaded binaries, scripts, applications, and other workloads. The platform supports checkpoint and restore, allowing environments to persist and resume instead of starting from scratch each time. Sprites use fast directly attached NVMe storage that continuously syncs to durable external object storage. Developers can create, manage, execute commands, and connect to Sprite consoles through the CLI, REST API, JavaScript, Go, Elixir, and Python tooling. Built for developers and AI infrastructure teams, Sprites gives applications a simple place to safely run code with persistence, sandboxing, usage-based pricing, and scalable execution.
  • 34
    xpander.ai

    xpander.ai

    xpander.ai

    xpander.ai is a backend-as-a-service platform tailored for production-grade AI agents, offering developers a robust infrastructure that handles memory, tools, connectors, multi-agent workflows, triggering, state management, observability, and CI/CD pipelines without requiring infrastructure setup. Its visual AI agent workbench enables users to design, configure, simulate, test, and deploy agents interactively, complete with support for multi-agent collaboration, tool integrations, role-based access, and runtime governance. Developers can connect agents to SaaS or enterprise systems via AI-ready connectors, attach tool-compatible workflows, and monitor agent behavior with built-in observability and lifecycle tools. It supports deployment on hosted cloud infrastructure or within private VPCs, ensuring both agility and secure enterprise integration, and accelerates agent development from idea to production.
  • 35
    Movestax

    Movestax

    Movestax

    Movestax revolutionizes cloud infrastructure with a serverless-first platform for builders. From app deployment to serverless functions, databases, and authentication, Movestax helps you build, scale, and automate without the complexity of traditional cloud providers. Whether you’re just starting out or scaling fast, Movestax offers the services you need to grow. Deploy frontend and backend applications instantly, with integrated CI/CD. Fully managed, scalable PostgreSQL, MySQL, MongoDB, and Redis that just work. Create sophisticated workflows and integrations directly within your cloud infrastructure. Run scalable serverless functions, automating tasks without managing servers. Simplify user management with Movestax’s built-in authentication system. Access pre-built APIs and foster community collaboration to accelerate development. Store and retrieve files and backups with secure, scalable object storage.
  • 36
    nebulon

    nebulon

    nebulon

    nebulon smartInfrastructure is server-embedded, infrastructure software delivered as-a-service, which offers self-service provisioning, infrastructure management and enterprise shared and local data services, across your entire on-prem deployment, anywhere for any application. Lengthy and complex software update procedures are an artifact of the past. Make use of new features and enhancements instantly through cloud-delivered software updates “as-a-service” – an experience that has yet to become mainstream in on-prem enterprise applications. Also, with AIOps, enjoy predictive maintenance and simplified troubleshooting. Plus get centralized server, storage, and application visibility that enables the necessary tooling of real-time detection of latent issues across your stack and the facilities for corrective measures.
  • 37
    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.
  • 38
    Strike48

    Strike48

    Strike48

    Strike48 is the Agentic Operations Platform combining complete log visibility with customizable AI agents that run security, IT, and compliance operations at machine speed. Most organizations monitor only about 60-70% of their environment because traditional SIEM and observability platforms make full log coverage cost-prohibitive. Strike48 closes that visibility gap with architecture that decouples storage from upfront parsing decisions, letting teams ingest and retain all their logs without breaking budgets. Bring your logs or query them where they already live (Splunk, data lakes, cloud, on-prem), no rip-and-replace required. On top of that unified data layer, Strike48 deploys autonomous AI agents that run investigations, correlate and triage alerts, collect evidence, generate and validate detection rules, and hand work off to each other. A human-in-the-loop model ensures people approve critical actions like endpoint isolation and remediation, with full audit trails.
  • 39
    Nimbus

    Nimbus

    Nimbus Intelligence, Inc.

    Nimbus is collaborative. It is one platform where your team communicates together, collaborates with AI agents, automates work in loops, and where executives govern and control how AI is used. Communicate: people talk on the work itself, the brief, the files, the decisions, instead of pasting drafts between private chats nobody can reconstruct later. Collaborate: teams and agents work on the same job. Agents help research, draft, and propose next steps. People stay in the room and finish together. Automate: once a job works, it can run as a loop, the same process, again, with people pulled in when a decision is needed. Not a one-off prompt. Work that keeps going. Govern: leaders can see who is using AI, set the rules for what it may do, and keep a named person in control before anything important is committed. Most companies already have AI in personal tools, side experiments, and pilots nobody owns.
  • 40
    Modular

    Modular

    Modular

    Modular is a unified AI inference platform designed to run models efficiently across diverse hardware environments. It enables developers to deploy and scale AI workloads on GPUs, CPUs, and ASICs using a single, integrated stack. The platform optimizes performance from low-level GPU kernels to high-level API endpoints. Modular supports both managed cloud deployments and self-hosted environments, offering flexibility for different use cases. It allows users to run open-source or custom models with high performance and cost efficiency. With features like hardware portability and dynamic scaling, it reduces vendor lock-in and infrastructure complexity. By combining performance optimization and deployment simplicity, Modular helps teams build and run AI applications at scale.
  • 41
    Crewship

    Crewship

    Crewship

    Crewship is the developer-first platform for deploying AI agent workflows. Deploy your CrewAI, LangGraph, and LangGraph.js agents with a single command and watch them execute in real-time. Key features include one-command deployment, real-time execution streaming, artifact management, auto-scaling, version control, and encrypted secrets management. Crewship handles infrastructure so developers can focus on building great AI agents. Multi-framework support with AutoGen, Pydantic AI, smolagents, OpenAI Agents, Mastra, and Agno coming soon.
  • 42
    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.
  • 43
    Reflexio

    Reflexio

    Reflexio

    Reflexio is an AI-agent learning platform for developers building and operating agents. It ingests agent interactions, execution traces, tool calls, and user corrections through an SDK, REST API, CLI, or supported tracing-platform connections, then extracts recurring failures into reusable playbooks and user profiles. At runtime, an agent can retrieve relevant learned guidance before responding. The Hosted Enterprise portal lets teams inspect, edit, approve, reject, search, and evaluate learnings. Reflexio helps agents apply corrections across interactions without changing model weights. Teams can use the managed cloud service, configure their own model-provider keys, or self-host in AWS, Google Cloud, or Azure. Enterprise trace imports are available from Braintrust, Langfuse Cloud, and LangSmith Cloud; Reflexio also provides a mem0 wrapper and an OpenClaw integration.
  • 44
    IBM watsonx.ai
    Now available—a next generation enterprise studio for AI builders to train, validate, tune and deploy AI models IBM® watsonx.ai™ AI studio is part of the IBM watsonx™ AI and data platform, bringing together new generative AI (gen AI) capabilities powered by foundation models and traditional machine learning (ML) into a powerful studio spanning the AI lifecycle. Tune and guide models with your enterprise data to meet your needs with easy-to-use tools for building and refining performant prompts. With watsonx.ai, you can build AI applications in a fraction of the time and with a fraction of the data. Watsonx.ai offers: End-to-end AI governance: Enterprises can scale and accelerate the impact of AI with trusted data across the business, using data wherever it resides. Hybrid, multi-cloud deployments: IBM provides the flexibility to integrate and deploy your AI workloads into your hybrid-cloud stack of choice.
  • 45
    VideoDB

    VideoDB

    VideoDB

    VideoDB is a modern backend for AI agents, giving them the ability to see, understand, and act on video and audio in real time. It sits between raw media streams and agent reasoning systems, turning continuous streams into structured, searchable context with playable evidence. Our unified See->Understand->Act workflow replaces a fragmented stack of FFmpeg, vector DBs, and transcription tools with a single, programmable media layer. Featuring "Indexes-as-code," we allow developers to extract meaning from spoken words and visual scenes with near-zero latency. VideoDB supports Python and Node.js SDKs and integrates seamlessly with Claude, Cursor, and Codex via the Model Context Protocol (MCP). Built on a streaming-first architecture, it ensures your agents observe the world continuously rather than just reading static files. Whether you are building an AI meeting copilot, camera intelligence, or automated media editing, VideoDB provides the perception layer you need.
  • 46
    Composio

    Composio

    Composio

    Composio is a platform that enables AI agents to seamlessly interact with external tools and applications. It provides pre-built integrations with over 1,000 apps, allowing agents to execute tasks across services like Slack, Gmail, GitHub, and more. The platform handles complex processes such as authentication, tool execution, and sandboxed environments automatically. Composio supports dynamic tool selection, ensuring agents use the right tools based on user intent. It also enables secure, parallel execution of workflows in isolated environments. Developers can build agents that move beyond conversation to perform real-world actions. By simplifying integrations and execution, Composio helps turn AI agents into powerful, task-performing systems.
  • 47
    Composio Instant
    Composio Instant is a cloud-based wallet that lets AI agents call paid tools without developers subscribing to each provider or configuring a separate API key for every service. Developers connect Instant to an agent session, choose which tools are available, and use a shared organization balance; charges are recorded in execution logs. Calls draw from that balance at a per-use rate, and new developer organizations receive a one-time $2 starter credit. Available services include web search, data enrichment, scraping, transcription, voice, weather, and document processing. Developers can connect through Composio’s SDKs and MCP-compatible agent clients, including Claude, ChatGPT, Codex, Cursor, Gemini CLI, Grok, and Visual Studio Code. Instant is intended for developers and teams building or operating AI agents that need on-demand access to external capabilities.
  • 48
    NVIDIA AI Enterprise
    The software layer of the NVIDIA AI platform, NVIDIA AI Enterprise accelerates the data science pipeline and streamlines development and deployment of production AI including generative AI, computer vision, speech AI and more. With over 50 frameworks, pretrained models and development tools, NVIDIA AI Enterprise is designed to accelerate enterprises to the leading edge of AI, while also simplifying AI to make it accessible to every enterprise. The adoption of artificial intelligence and machine learning has gone mainstream, and is core to nearly every company’s competitive strategy. One of the toughest challenges for enterprises is the struggle with siloed infrastructure across the cloud and on-premises data centers. AI requires their environments to be managed as a common platform, instead of islands of compute.
  • 49
    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.
  • 50
    Ovrin
    Ovrin is a hosted compute platform for developers building AI agents and software that needs to run code in controlled environments. Through a REST API, Python and TypeScript SDKs, or an MCP server, users can create disposable Linux sandboxes, run shell commands and stateful code, manage files and scoped API keys, and retrieve execution output. Preconfigured environments include Claude Code, OpenAI Codex, Gemini CLI, and DeepSeek Harness; browser workflows can use Chrome and Playwright. The platform also offers persistent memory, sandbox lifecycle controls, usage metering, and concurrency limits. Typical uses include coding-agent execution, browser automation, and running model-generated code. Plans include a free tier and paid tiers with additional concurrency and usage-based compute charges.