Inspect · scoring run
Mirador Architecture · 284f114c
Account
Mirador Architecture
AEC · tier Build
Overall
70
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": 70,
"segment": "industries",
"why_now": {
"date": "2026-06-09",
"type": "product_launch",
"label": "Shipped agent-powered workflow",
"detail": "Captured from public sources during nightly pass.",
"source_url": "https://example.com/whynow/2baf72b4",
"source_type": "investors"
},
"industry": "",
"use_case": "",
"comparable": "",
"confidence": "medium",
"dimensions": [
{
"key": "kw_density",
"name": "Knowledge-Worker Density",
"score": 65,
"rationale": "Reading/writing heavy workforce",
"evidence_refs": [
3
]
},
{
"key": "public_ai_commitment",
"name": "Public AI Commitment",
"score": 74,
"rationale": "Earnings-call AI mentions trending",
"evidence_refs": [
1
]
},
{
"key": "workflow_volume",
"name": "Automatable Workflow Volume",
"score": 69,
"rationale": "High-volume repeatable knowledge tasks",
"evidence_refs": [
1
]
},
{
"key": "transformation_readiness",
"name": "Transformation Readiness",
"score": 71,
"rationale": "Recent platform consolidation",
"evidence_refs": [
3
]
},
{
"key": "sector_velocity",
"name": "Sector AI Velocity",
"score": 75,
"rationale": "Investor questions on AI per call",
"evidence_refs": [
2
]
}
]
}Parse · five dimensions
Analyst-dominant org chart
Earnings-call AI mentions trending
Manual triage compressible
Active change-mgmt practice
Competitive pressure rising
Evidence pack · 3
Open roles include Senior ML, Forward Deployed Engineer, AI PM. Hiring across NA + EMEA.
fetched 6/14/2026 · dims: sector_velocity, public_ai_commitment
Company announced a multi-year AI transformation program with executive sponsorship.
fetched 6/4/2026 · dims: transformation_readiness, sector_velocity
New executive role created to own AI strategy across business units.
fetched 5/27/2026 · dims: transformation_readiness, workflow_volume