Cloud World Model
    For AI agents & builders
    Infrastructure & platform teams · architects
    Patent Pending

    See how an infrastructure change behaves before you merge

    Connect a GitHub repo and Cloud World Model comments a simulation on the pull request. It models p99 latency, error rate, traffic spikes, node and zone failures and recovery, and cost. It never connects to your cloud.

    • Sign in, connect a repo, and comment /cwm simulate, or the next infra PR gets a report.
    • Each simulation covers how the change behaves under load and failure, including p99 latency, error rate, traffic spikes, and node or zone loss and recovery, plus cost.
    • CWM never connects to your cloud. It supports AWS, Azure, GCP, Oracle Cloud (OCI), and DigitalOcean, and agents can use the same simulation over MCP or the API.
    Connect a GitHub repo

    1,000 free credits every 30 days; no card required.

    See an example report
    ExploreBrowse ScenariosTry Interactive DemoUse CasesPricing TrendsAPI DocsAgent DocsWatch Demo
    terraform.pr-report
    Excerpt · modeled comparison

    Cloud World Model — Infrastructure Simulation Report

    Terraform pull request
    Before and after values from the source simulation report.
    Modeled total cost per hourBefore$0.73/hr (modeled)After$0.80/hr (modeled)Change+$0.07/hr
    p99 latencyBefore373ms (uncalibrated reference estimate)After277ms (uncalibrated reference estimate)Change-96ms
    Error rateBefore6.00%After0.00%Change-6.00 percentage points
    ResilienceBefore0/100 (modeled)before fixAfter76/100 (modeled)Change+76 score points
    Real Terraform PR report at 300 RPS, modeled with no cloud account access. Not a production guarantee.

    Modeled verdict: about $0.07/hr more, p99 down about 96ms, errors 6% → 0% at 300 RPS, resilience 0 → 76. Review before shipping.

    ProvidersAWSGCPAzureOCIDigitalOcean
    No real cloud provisioning
    Zero Infrastructure Costs
    Instant Setup
    Agent & Headless Ready
    Measured evidence, stated limits

    See what the simulation is measured against

    Our accuracy benchmark compares simulated results with an owned AWS load-test campaign at 10, 100, 500, and 1,000 requests per second. Cost is compared against the public price list; other providers use documentation references, not the same owned measurement. Scores describe this benchmark architecture, not a guarantee for every workload.

    The PR report above uses a synthetic 300 RPS comparison workload, not an additional measured AWS campaign test point; its GKE performance estimates are uncalibrated.

    Explore measured accuracyReview fidelity and limitsRead the benchmark report

    Get your first infrastructure PR report

    Connect GitHub to see modeled cost, performance and resilience changes before you merge.

    Connecting is free. Each PR comparison uses 10 CWM credits.

    Connect GitHub repositorySee an example report
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    Featured & Recognized

    Product Hunt daily top-post badge for Cloud World Model

    See It In Action

    Watch how Cloud World Model simulates real cloud infrastructure behavior — without provisioning a single resource.

    Recorded simulation run Demo

    World Model Capabilities

    Advanced AI models predict infrastructure behavior with physics-informed constraints and learned dynamics

    01
    Real-time Simulation
    Predict latency, throughput, and cost with physics-informed AI models
    02
    Failure Injection
    Test resilience with AZ outages, traffic spikes, and node failures
    03
    Cost Optimization
    Train RL agents to minimize costs while maintaining performance
    04
    Multi-Cloud Support
    Simulate AWS, GCP, Azure, OCI, and DigitalOcean with provider-specific behavior

    Who It's For

    For agent builders first, then infrastructure and platform teams and cloud architects

    AI Agent Builders

    Give agents a safe environment to compare infrastructure actions before deploying or changing infrastructure

    Learn more
    Infrastructure & Platform Teams

    Help teams and architects assess cost, latency, errors, and resilience before rollout

    Learn more
    Cost Optimization

    Predict and minimize cloud spending with AI-powered simulations

    Learn more
    Chaos Engineering

    Use controlled, simulated failures to estimate cost, latency, errors, and resilience before deploying or changing real infrastructure. Simulated chaos informs hypotheses; it does not replace production fault injection.

    Learn more
    Multi-Cloud Strategy

    Compare providers and traffic splits against cost, latency, and resilience goals

    Learn more
    Supports x402
    Linux Foundation Protocol
    AI agents can call any API endpoint without signing up — pay per call in USDC on Base. No account, no API key required.

    Network

    Base (Ethereum L2)

    Asset

    USDC

    Discovery

    /api/billing/x402/config

    Learn more about agent accessAvailable on x402scan

    Agent Storefront on TryPoncho

    For AI Agents

    The Cloud World Model merchant page on TryPoncho lists all x402-priced endpoints, live pricing, the curated OpenAPI spec, and AgentCash integration — a single machine-readable index for autonomous agents discovering this API.

    Open Agent Storefront

    Connect via MCP

    For AI Assistants

    Connect any MCP client directly to https://www.cloudworldmodel.ai/mcp. Omit the API key for the capped keyless demo, or send your CWM key in the x-api-key header.

    MCP Quick Start

    What Engineers Are Saying

    Engineers and leaders reacting to the launch on Product Hunt and LinkedIn

    Product Hunt #5 Product of the Day — 179 upvotes and 61 comments (historical snapshot recorded June 29, 2026; not live counts).

    Simulation lets teams explore ideas before committing resources. Finding weaknesses before deployment is almost always less expensive than discovering them in production.

    Gennadiy Vaksman

    Technology & Business Leader / Advisor

    From LinkedIn ↗

    Cloud mistakes usually get expensive after you already deployed them. Being able to play with failure scenarios, cost, and scaling before touching real infra feels especially useful for learners and small teams that don't have a proper staging setup.

    Alper Tayfur

    View on Product Hunt ↗

    Cost avoidance during cloud experimentation has always been a silent constraint in engineering teams. Digital twin style environments change exploration economics in a meaningful way.

    Paul Storm

    Co-Founder, Dr. Storm Advisory GmbH

    From LinkedIn ↗

    Cost is the question that never really leaves the room, and almost always the hardest thing to pin down before you commit.

    Kévin Monteiro

    View on Product Hunt ↗

    Chaos engineering with resilience scoring before touching real infra is a great fit for teams that want to test failure modes without blowing a staging budget.

    Xi Chiwoo

    View on Product Hunt ↗

    If simulation becomes reliable enough, it could seriously change how teams approach pre-production testing.

    Thomas Hoon

    China-ASEAN Market Entry Strategist

    From LinkedIn ↗

    My 'test' is deploy-and-pray, no real staging. The failures that hurt are the silent ones, not the loud ones.

    David

    View on Product Hunt ↗

    Ready to Start Simulating?

    Build, test, and optimize cloud architectures without the risk or cost

    Start a Free SimulationView Pricing