Inspect · scoring run
Aurum Mining · 17905fe0
model · google/gemini-2.5-prosegment · industriesconfidence · mediumevidence · 3latency · 2.75 sat · 6/16/2026, 2:00:00 PM
Account
Aurum Mining
Mining · tier Build
Overall
66
Prompt
score-account-industries · v1
You are scoring an industries account (financial services, healthcare, retail, manufacturing) against the Anthropic field rubric. Score each 0-100 with a one-line cited rationale: 1. Knowledge-Worker Density — share of workforce doing reading, writing, analysis (law firms high, manufacturing lower) 2. Public AI Commitment — measured via open roles, exec statements, press releases 3. Automatable Workflow Volume — volume of repetitive knowledge work Claude could compress 4. Transformation Readiness — data, tooling, change-management maturity to deploy 5. Sector AI Velocity — how fast peers in the sector are moving — competitive pressure Same JSON shape as the tech rubric. Confidence "high" only with three live-evidence dimensions.
Raw response
exactly what Claude returned
{
"tier": "Build",
"notes": "",
"company": "<see accounts.name>",
"overall": 66,
"segment": "industries",
"why_now": {
"date": "2026-05-29",
"type": "press_release",
"label": "Announced AI transformation program",
"detail": "Captured from public sources during nightly pass.",
"source_url": "https://example.com/whynow/023a4d49",
"source_type": "linkedin"
},
"industry": "",
"use_case": "",
"comparable": "",
"confidence": "medium",
"dimensions": [
{
"key": "kw_density",
"name": "Knowledge-Worker Density",
"score": 74,
"rationale": "Analyst-dominant org chart",
"evidence_refs": [
2
]
},
{
"key": "public_ai_commitment",
"name": "Public AI Commitment",
"score": 64,
"rationale": "AI roles open + exec quotes",
"evidence_refs": [
2
]
},
{
"key": "workflow_volume",
"name": "Automatable Workflow Volume",
"score": 63,
"rationale": "Manual triage compressible",
"evidence_refs": [
2
]
},
{
"key": "transformation_readiness",
"name": "Transformation Readiness",
"score": 66,
"rationale": "Active change-mgmt practice",
"evidence_refs": [
1
]
},
{
"key": "sector_velocity",
"name": "Sector AI Velocity",
"score": 58,
"rationale": "Investor questions on AI per call",
"evidence_refs": [
2
]
}
]
}Parse · five dimensions
Knowledge-Worker Density61
Document-bound day-to-day
Public AI Commitment67
Earnings-call AI mentions trending
Automatable Workflow Volume67
Manual triage compressible
Transformation Readiness71
Recent platform consolidation
Sector AI Velocity70
Investor questions on AI per call
Evidence pack · 3
Open roles include Senior ML, Forward Deployed Engineer, AI PM. Hiring across NA + EMEA.
fetched 6/16/2026 · dims: sector_velocity, kw_density
AI named as a top-3 priority in latest investor communication.
fetched 6/6/2026 · dims: transformation_readiness, sector_velocity
Company announced a multi-year AI transformation program with executive sponsorship.
fetched 6/1/2026 · dims: workflow_volume, kw_density