Compute · Assess & Decide · Data & Research

Score an AI idea's business feasibility on 1-4 scales

A founder comparing AI product ideas gets a defensible 1-4 score on each business-feasibility dimension and an average, derived from concrete inputs (SOM, usage cadence, validation %, scalability), so ideas can be ranked on a like-for-like basis.

You receive: A pure function returning the four 1-4 sub-scores (market size, usage frequency, market need, scalability) and their mean, from the SOM, cadence, validation share, scalability tier, and your band edges, graded on hidden cases.

Part of Choose Business Model

What's verified: STUD verifies each of the four sub-scores is the correct 1-4 value from the banded inputs and that the composite is the correct mean, on held-out cases. STUD does NOT verify that the SOM figure, usage cadence, validation percentage, or scalability tier are accurate for the real idea, nor that a high score means the idea will make money.

Opens soon

Cost20 credits

AcceptanceAutomated check against your inputs

ProtectionHeld until verified delivery

This objective is verified and ready. It opens soon, once sign-in and payments are live.

Deliverable interface

The exact vocabulary the automated check enforces: keys, tokens, entry points, and worked examples. Generated from the verification source.

{
 "constants": {},
 "entryName": "compute_ai_idea_business_feasibility",
 "expectNote": "expect is the comparison-space value (your return value goes through normalize first when one is published)",
 "hiddenCaseCount": 14,
 "hiddenCaseNames": [
  "hd_som_at_edge1",
  "hd_som_just_below_edge1",
  "hd_val_at_edge2",
  "hd_som_at_edge3",
  "hd_custom_edges",
  "hd_val_zero",
  "gen0",
  "gen1",
  "gen2",
  "gen3",
  "gen4",
  "gen5",
  "gen6",
  "gen7"
 ],
 "inputKeys": [
  "scalabilityTier",
  "somEdge1",
  "somEdge2",
  "somEdge3",
  "somUsd",
  "usageCadence",
  "valEdge1",
  "valEdge2",
  "valEdge3",
  "validationPct"
 ],
 "normalizeSource": "def _normalize_ai_idea_business_feasibility(r):\n    if not isinstance(r, dict):\n        return repr(r)\n    try:\n        return {\"marketSize\": int(round(float(r[\"marketSize\"]))), \"usageFrequency\": int(round(float(r[\"usageFrequency\"]))),\n                \"marketNeed\": int(round(float(r[\"marketNeed\"]))), \"scalability\": int(round(float(r[\"scalability\"]))),\n                \"composite\": round(float(r[\"composite\"]), 2)}\n    except Exception:\n        return repr(r)\n",
 "returnShapes": [
  [
   "composite",
   "marketNeed",
   "marketSize",
   "scalability",
   "usageFrequency"
  ]
 ],
 "signature": "def compute_ai_idea_business_feasibility(inp):",
 "submission": "python exposing the entry function; inp is one input object; graded on held-out cases",
 "tier": "calculator",
 "visibleCases": [
  {
   "expect": {
    "composite": 4,
    "marketNeed": 4,
    "marketSize": 4,
    "scalability": 4,
    "usageFrequency": 4
   },
   "input": {
    "scalabilityTier": "massive",
    "somEdge1": 100000,
    "somEdge2": 1000000,
    "somEdge3": 10000000,
    "somUsd": 50000000,
    "usageCadence": "continuous",
    "valEdge1": 25,
    "valEdge2": 50,
    "valEdge3": 75,
    "validationPct": 80
   },
   "name": "all_max"
  },
  {
   "expect": {
    "composite": 1,
    "marketNeed": 1,
    "marketSize": 1,
    "scalability": 1,
    "usageFrequency": 1
   },
   "input": {
    "scalabilityTier": "single",
    "somEdge1": 100000,
    "somEdge2": 1000000,
    "somEdge3": 10000000,
    "somUsd": 50000,
    "usageCadence": "monthlyOrLess",
    "valEdge1": 25,
    "valEdge2": 50,
    "valEdge3": 75,
    "validationPct": 10
   },
   "name": "all_min"
  },
  {
   "expect": {
    "composite": 2.5,
    "marketNeed": 3,
    "marketSize": 3,
    "scalability": 2,
    "usageFrequency": 2
   },
   "input": {
    "scalabilityTier": "few",
    "somEdge1": 100000,
    "somEdge2": 1000000,
    "somEdge3": 10000000,
    "somUsd": 5000000,
    "usageCadence": "weekly",
    "valEdge1": 25,
    "valEdge2": 50,
    "valEdge3": 75,
    "validationPct": 60
   },
   "name": "mixed"
  },
  {
   "expect": {
    "composite": 3.25,
    "marketNeed": 4,
    "marketSize": 3,
    "scalability": 3,
    "usageFrequency": 3
   },
   "input": {
    "scalabilityTier": "many",
    "somEdge1": 100000,
    "somEdge2": 1000000,
    "somEdge3": 10000000,
    "somUsd": 1000000,
    "usageCadence": "daily",
    "valEdge1": 25,
    "valEdge2": 50,
    "valEdge3": 75,
    "validationPct": 75
   },
   "name": "boundaries_at_edge"
  }
 ],
 "vocabulary": [
  "composite",
  "continuous",
  "daily",
  "few",
  "many",
  "marketNeed",
  "marketSize",
  "massive",
  "monthlyOrLess",
  "scalability",
  "scalabilityTier",
  "single",
  "somEdge1",
  "somEdge2",
  "somEdge3",
  "somUsd",
  "usageCadence",
  "usageFrequency",
  "valEdge1",
  "valEdge2",
  "valEdge3",
  "validationPct",
  "weekly"
 ]
}

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