Full Deployment
Planner
Define your complete deployment scenario across all dimensions. The engine calculates hardware, power infrastructure, network bandwidth, and storage endurance — and outputs a full bill of materials with cost estimates.
// Define deployment
// Bill of Materials
What this Full Deployment Planner decides
This planner is the deployment-level decision layer for EdgeAIStack. It combines compute selection, power infrastructure, network sizing, storage retention, enclosure requirements, and installation cost into a single deployment specification. The goal is to turn a scenario description into a practical, machine-readable bill of materials for real edge AI deployments.
Use case and AI model type determine the practical compute profile and deployment shape.
Stream count and resolution drive compute demand, network bandwidth, and storage growth.
Power method, storage retention, and deployment environment shape the infrastructure bill of materials and total project cost.
The planner takes the selected deployment inputs and generates a full-system estimate across the major infrastructure layers needed for edge AI: compute hardware, network switching, power delivery, storage media, enclosures, and installation. The result is designed to help engineers and buyers move from idea to deployment specification faster.
- Compute platform recommendation and quantity
- Network switch and cabling estimate
- Power infrastructure class and load planning
- Storage capacity and endurance fit
- Environmental enclosure guidance
- Installation and project-level cost estimate
The output groups costs and components into deployment sections so the result is readable by both humans and downstream systems. It is intended as a planning BOM rather than a final quote.
- Summary layer: project cost, hardware cost, power draw, network bandwidth, storage requirement, and selected accelerator
- BOM sections: compute, network, power, storage, enclosure, and installation
- Warnings layer: constraints such as tight compute headroom, storage fit risk, power limits, or bandwidth bottlenecks
- Machine-readable layer: exportable JSON for configuration reuse, sharing, or API-based workflows
{
"tool": "full-deployment-planner",
"schema_version": "v1",
"inputs": {
"scenario": "security",
"cameras": 8,
"resolution": "1080p",
"model": "detection",
"power_infra": "poe",
"retention": 30,
"environment": "outdoor_sheltered"
},
"outputs": {
"summary": {
"total_project_cost": 4250,
"hardware_cost": 3530,
"total_power_w": 140,
"network_mbps": 48,
"storage_tb": 15.4,
"accelerator": "Jetson Orin Nano"
},
"bill_of_materials": [
{
"item": "Jetson Orin Nano",
"qty": 2,
"est_cost_usd": 998
},
{
"item": "Managed PoE Switch",
"qty": 1,
"est_cost_usd": 220
},
{
"item": "NVMe Storage",
"qty": 2,
"est_cost_usd": 320
}
]
}
}
// FAQ
Is this the main planning tool on the site?
Yes. This is the deployment-level tool that brings together the reasoning from the individual hardware, power, network, and storage calculators into one consolidated planning output.
Does the bill of materials include installation?
Yes. The planner includes an installation estimate as part of the deployment-level total, though it should be treated as a planning-grade estimate rather than a final services quote.
Can the output be shared or reused?
Yes. The planner produces machine-readable JSON output and supports shareable configurations so the deployment can be reviewed, exported, or reused in downstream workflows.
Should I send the second file too?
If the slug has an additional file that renders saved configurations, print views, or deployment-specific output pages, that file is worth reviewing too because it likely affects crawlability and how AI systems interpret saved deployment specs.