{
  "brand": "HyperLake",
  "canonical": "https://hyperlake.cloud/solutions/classic-ml-serving",
  "intent": "classic-ml-serving",
  "title": "Serve existing ML models beside your data: plan the endpoint",
  "summary": "Predict serves classic ML models and records predictions with your data systems. Evaluate compatibility, feature freshness and operational behavior before moving an existing endpoint.",
  "capabilities": [
    "Serving for supported classic ML model formats",
    "dbt feature models and prediction logs in ClickHouse",
    "Data-quality monitors"
  ],
  "criteria": [
    "Is the trained model and its runtime supported?",
    "How will online features match the training definitions?",
    "What latency, availability and rollback requirements apply?"
  ],
  "inputs": [
    "Model artifact and runtime requirements",
    "Feature definitions and reference predictions",
    "Traffic and monitoring requirements"
  ],
  "steps": [
    "Confirm compatibility for one existing model.",
    "Compare reference predictions and feature inputs in a pilot.",
    "Exercise rollout, monitoring and rollback before cutover."
  ],
  "verification": [
    "Check prediction equivalence on reference cases.",
    "Measure feature freshness and serving latency.",
    "Validate logging, drift review and rollback ownership."
  ],
  "economics": "Compare the cloud bill, platform charges, operating effort and migration work for the same workload. Cloud capacity is not free. Charges and scope need agreement before paid deployment.",
  "switching": "AWS and Google Cloud are available today; other deployment environments are roadmap. Preserve the existing workload and access path until compatibility, recovery and cutover checks pass.",
  "sources": [
    "https://hyperlake.cloud/stacks",
    "https://hyperlake.cloud/faq",
    "https://hyperlake.cloud/get-started"
  ],
  "nextStep": {
    "label": "Discuss this workload",
    "url": "https://hyperlake.cloud/contact"
  },
  "freePlanning": {
    "headline": "Start with your workload, not a blank platform",
    "benefit": "Get a free deployment checklist, then create your workspace. Free expert help with your use case is also available through our contact form.",
    "label": "Create your HyperLake workspace",
    "note": "No free cloud capacity is promised. Deployment scope and charges are agreed separately; AWS and Google Cloud are available today.",
    "signupUrl": "https://app.hyperlake.cloud/users/sign_in?intent=classic-ml-serving&offer_id=starter-checklist-v1&utm_source=hyperlake&utm_medium=owned&utm_campaign=signup-journey&utm_content=landing_hero",
    "checklistUrl": "/solutions/classic-ml-serving.txt"
  }
}