Data & AI Platform Blueprint Slide Template
Data and AI platform architecture: ingestion through storage, processing, and hero intelligence services up to consumption. Downward tonal ramp shows platform flow. Data sources on the left, consumers on the right or design-principles panel. Warm accent reserved for governance/model-risk cross-cutting. Best for lakehouse blueprints, AI operating model slides, analytics platform overviews, semantic-layer architecture, and AI-factory diagrams.
Try in PlaygroundParameters
Example brief
Target data & AI platform: ingestion (batch, CDC, streaming, API), storage (lakehouse, operational store, metadata), processing (ETL, orchestration, quality), Data & AI Services (semantic layer, feature store, ML, vector search), consumption (dashboards, apps, reporting, AI copilots). Sources on the left, governance/observability/model risk cross-cutting, 3 design principles on the right.
API example
With a brief (async, $0.05)
curl -X POST https://api.slideforge.dev/v1/render \
-H "Authorization: Bearer sf_live_..." \
-H "Content-Type: application/json" \
-d '{
"template": "a8578b52-49c0-5848-a04e-4ee19ef83815",
"brief": "Target data & AI platform: ingestion (batch, CDC, streaming, API), storage (lake..."
}'With structured params (sync, $0.03)
curl -X POST https://api.slideforge.dev/v1/render \
-H "Authorization: Bearer sf_live_..." \
-H "Content-Type: application/json" \
-d '{
"template": "a8578b52-49c0-5848-a04e-4ee19ef83815",
"params": {
"title": "Target data & AI platform — ingestion to intelligence",
"layers": [
{
"id": "consumption",
"label": "Consumption",
"description": "Business products + interfaces",
"items": [
{
"id": "dashboards",
"label": "BI Dashboards"
},
{
"id": "operational_apps",
"label": "Operational Apps"
},
{
"id": "executive_reports",
"label": "Executive Reporting"
},
{
"id": "copilots",
"label": "AI Copilots",
"emphasis": "high"
}
]
},
{
"id": "ai_services",
"label": "Data & AI",
"description": "Reusable intelligence services",
"items": [
{
"id": "semantic_layer",
"label": "Semantic Layer",
"emphasis": "high"
},
{
"id": "feature_store",
"label": "Feature Store"
},
{
"id": "ml_models",
"label": "ML Models"
},
{
"id": "vector_search",
"label": "Vector Search"
}
]
},
{
"id": "processing",
"label": "Processing",
"description": "Transform + orchestration",
"items": [
{
"id": "etl_elt",
"label": "ETL / ELT Pipelines"
},
{
"id": "orchestration",
"label": "Workflow Orchestration"
},
{
"id": "data_quality",
"label": "Data Quality"
},
{
"id": "business_rules",
"label": "Business Rules"
}
]
},
{
"id": "storage",
"label": "Storage",
"description": "Structured + unstructured data",
"items": [
{
"id": "lakehouse",
"label": "Lakehouse"
},
{
"id": "operational_store",
"label": "Operational Store"
},
{
"id": "metadata",
"label": "Metadata Catalog"
},
{
"id": "document_store",
"label": "Document Store"
}
]
},
{
"id": "ingestion",
"label": "Ingestion",
"description": "Batch + streaming ingestion",
"items": [
{
"id": "batch_ingest",
"label": "Batch Ingestion"
},
{
"id": "cdc",
"label": "CDC"
},
{
"id": "streaming",
"label": "Streaming Events"
},
{
"id": "api_ingestion",
"label": "API Ingestion"
}
]
}
],
"external_left": {
"id": "data_sources",
"label": "Data Sources",
"items": [
{
"id": "erp",
"label": "ERP"
},
{
"id": "crm",
"label": "CRM"
},
{
"id": "iot",
"label": "IoT"
},
{
"id": "files",
"label": "Files"
},
{
"id": "third_party",
"label": "3rd-Party"
}
]
},
"cross_cutting": [
{
"id": "security",
"label": "Security & Access"
},
{
"id": "governance",
"label": "Governance"
},
{
"id": "observability",
"label": "Observability"
},
{
"id": "model_risk",
"label": "Model Risk Mgmt"
}
],
"commentary": {
"title": "Design principles",
"items": [
{
"id": "p1",
"label": "Separate persistent storage from transformation so data assets remain reusable"
},
{
"id": "p2",
"label": "Expose reusable AI services through a governed semantic layer, not point pipelines"
},
{
"id": "p3",
"label": "Treat governance, observability, and model risk as platform controls across the stack"
},
{
"id": "p4",
"label": "Decouple ingestion from consumption so they evolve at different rates"
}
]
},
"takeaway": "Centralising storage + intelligence while decoupling ingestion and consumption scales platform reuse."
}
}'Tags
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Frequently asked questions
How do I render a Data & AI Platform Blueprint slide?
Send a POST request to /v1/render with template "a8578b52-49c0-5848-a04e-4ee19ef83815" and your data in the params field. The response includes a .pptx download URL and PNG preview. Template renders cost $0.03 and complete in under 1 second.
What data does the Data & AI Platform Blueprint template accept?
The Data & AI Platform Blueprint template accepts: title, layers, external_left, external_right, cross_cutting, commentary, takeaway. Supports 3-7 items. See the parameter reference below for details.
Can I customize the colors and fonts of this template?
Yes — pass a theme_id parameter to apply your custom brand colors, fonts, and logo. SlideForge has 8 built-in themes, or you can create custom themes via the Themes API.
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