HyperLake — Physical AI infrastructure and open-source stack map
FREE PLANNING CHECKLIST

Map the software layers needed for physical AI and robotics infrastructure.

Prepare these inputs
[ ] Sensor/data sources and intended deployment environment
[ ] Hardware, models and integration requirements
[ ] Safety, latency, data retention and operational ownership constraints

Your first workflow
[ ] Map the target workflow to the infrastructure layers.
[ ] Review official project references and identify missing integrations.
[ ] Test a bounded non-production pipeline on representative data.
[ ] Agree deployment scope and specialist responsibilities before production use.

Acceptance checks
[ ] Validate data formats and hardware compatibility.
[ ] Measure pipeline latency and recoverability.
[ ] Confirm domain-specific safety review and operating ownership.

Decision criteria
[ ] Map ingestion, storage, training, simulation, serving and observability as separate infrastructure layers.
[ ] Hardware compatibility, safety requirements and deployment environment constrain the software choice.
[ ] Treat the stack map as a planning aid; confirm project maturity, licenses and operational support directly.

Cost and scope
Evaluate infrastructure capacity and the work required to operate the selected components. Open-source licensing alone does not determine total cost.

Before switching
Check hardware, data formats, integration needs and operational ownership for your specific deployment.

Sources
https://hyperlake.cloud/physical-ai/open-source-stack-map
https://hyperlake.cloud/physical-ai

Next step
No free cloud capacity is promised. Deployment scope and charges are agreed separately; AWS and Google Cloud are available today.
https://hyperlake.cloud/solutions/physical-ai

This is a planning template, not a completed assessment or a quote. No personal data is required to download it.