{
  "docId": "019dd923-5fec-763b-95d0-77ce4047819f",
  "docSlug": "bi-2e15f648270c87d4",
  "documentTitle": "Machine-learning model startup Aporia raises $25 million: pitch deck",
  "authorId": "Pitchdecks",
  "authorName": "Aporia",
  "documentKindSlug": "pitchdeck",
  "documentKindLabel": "Pitch deck",
  "sourceTypeSlug": "strategy_consulting",
  "sourceTypeLabel": "Strategy consulting",
  "presentationDate": null,
  "orientation": "landscape",
  "aspectRatio": 1.777,
  "pageNumber": 4,
  "pageCount": 12,
  "prevPage": 3,
  "nextPage": 5,
  "slideType": "why_now",
  "function": "argue_timing",
  "density": "dense",
  "nDataPoints": 6,
  "notes": "Includes two bar charts showing market growth projections for MLOps and AI platforms.",
  "elementsJson": [
    "headline_text",
    "bullet_list",
    "bar_chart_vertical"
  ],
  "metadataConfidence": 1,
  "imagePath": null,
  "slideHref": "/slides/019dd923-5fec-763b-95d0-77ce4047819f/4",
  "deckHref": "/decks/019dd923-5fec-763b-95d0-77ce4047819f",
  "deckJsonHref": "/decks/019dd923-5fec-763b-95d0-77ce4047819f.json",
  "deckAnchorHref": "/decks/019dd923-5fec-763b-95d0-77ce4047819f#slide-4",
  "components": [
    {
      "bbox": {
        "h": 0.35,
        "w": 0.232,
        "x": 0.732,
        "y": 0.155
      },
      "kind": "chart",
      "text": "Machine Learning Operations market growth from $350M in 2019 to $4B in 2025 (CAGR 50%)",
      "attrs": null,
      "subkind": "bar-vertical",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "9d101d89-f2f1-46f4-973b-2a073faee84f",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.35,
        "w": 0.232,
        "x": 0.732,
        "y": 0.575
      },
      "kind": "chart",
      "text": "AI Platform & Developer Tools market growth from $2.1B in 2016 to $9.8B in 2022 (CAGR 31%)",
      "attrs": null,
      "subkind": "bar-vertical",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "ad7a92a3-1d27-4a5b-b6bc-604d1305385d",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.65,
        "w": 0.6,
        "x": 0.04,
        "y": 0.18
      },
      "kind": "list",
      "text": "Massive deployments of ML Models in production (most organizations have more than 25 models in production)\nML infrastructure has become more mature with many moving parts in production\nApril 2021 - AI is becoming regulated with the European Union draft for AI regulation\nMLOps is on the rise with ML Engineer being the most sought-after job on LinkedIn. Demand grew by 504% since 2017.",
      "attrs": null,
      "subkind": "bullet",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "7b3a1836-9275-4d31-a403-b4cb0c2cc265",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": null,
      "kind": "metric",
      "text": "Market Size: $4B",
      "attrs": null,
      "subkind": "primary",
      "toolName": "Quantification",
      "toolSlug": "quantification",
      "confidence": null,
      "componentId": "019dd952-b11a-739e-809f-271b377c5dcf",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.08,
        "w": 0.2,
        "x": 0.04,
        "y": 0.03
      },
      "kind": "title",
      "text": "Why Now?",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "45b8b328-b0ab-4ecf-96e5-b6d1503e11c3",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [],
  "tools": [],
  "frameworks": [
    {
      "name": "why-now",
      "slug": null,
      "matchId": "ad188453-af4d-48c5-847b-b8123fdb65cd",
      "evidence": "Slide title and content structure",
      "confidence": 1
    }
  ],
  "arcBeats": [
    {
      "to": 7,
      "from": 3,
      "beatId": "2e39371e-b118-466e-8b56-dea7832e9f7a",
      "arcName": "Problem-Agitate-Solution",
      "arcSlug": "problem-agitate-solution",
      "beatName": "Problem",
      "beatSlug": "problem-agitate-solution-problem-identify-pain",
      "evidence": "Slides 3-7 focus on the problem of ML models failing in production",
      "position": 0,
      "confidence": 0.9,
      "parentBeatName": "Complication",
      "parentBeatSlug": "complication"
    }
  ],
  "loops": [
    {
      "to": 7,
      "from": 4,
      "name": "Cost Of Inaction",
      "slug": "27-cost-of-inaction",
      "bestFor": "Urgent budget requests, compliance, risk mitigation",
      "matchId": "b9a7f297-86d2-48e5-9c3a-659c36ca5feb",
      "evidence": "Slides 4-7 create a sense of urgency",
      "position": 0,
      "objective": "Why now?",
      "structure": "The Status Quo -> The Hidden Costs Accumulating -> The Future State of Inaction -> The Tipping Point",
      "confidence": 0.7,
      "description": "Quantify what happens if the audience does nothing"
    }
  ],
  "imagePathAlt": null,
  "thumbSrc": null,
  "thumbSrcAlt": null,
  "locked": true
}