Runs

Inspect · scoring run

Capstone Construction · 6ae63979

model · google/gemini-2.5-prosegment · industriesconfidence · highevidence · 3latency · 2.52 sat · 6/16/2026, 9:00:00 PM

Account

Capstone Construction

Construction · tier Priority

Overall

83

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": "Priority",
  "notes": "",
  "company": "<see accounts.name>",
  "overall": 83,
  "segment": "industries",
  "why_now": {
    "date": "2026-05-27",
    "type": "regulatory",
    "label": "Regulator update forces process redesign",
    "detail": "Captured from public sources during nightly pass.",
    "source_url": "https://example.com/whynow/94561b51",
    "source_type": "investors"
  },
  "industry": "",
  "use_case": "",
  "comparable": "",
  "confidence": "high",
  "dimensions": [
    {
      "key": "kw_density",
      "name": "Knowledge-Worker Density",
      "score": 75,
      "rationale": "Analyst-dominant org chart",
      "evidence_refs": [
        1
      ]
    },
    {
      "key": "public_ai_commitment",
      "name": "Public AI Commitment",
      "score": 79,
      "rationale": "Earnings-call AI mentions trending",
      "evidence_refs": [
        3
      ]
    },
    {
      "key": "workflow_volume",
      "name": "Automatable Workflow Volume",
      "score": 91,
      "rationale": "Backlog of structured drafting work",
      "evidence_refs": [
        1
      ]
    },
    {
      "key": "transformation_readiness",
      "name": "Transformation Readiness",
      "score": 84,
      "rationale": "Data + governance maturity present",
      "evidence_refs": [
        2
      ]
    },
    {
      "key": "sector_velocity",
      "name": "Sector AI Velocity",
      "score": 78,
      "rationale": "Peers shipping AI features fast",
      "evidence_refs": [
        1
      ]
    }
  ]
}

Parse · five dimensions

Knowledge-Worker Density
79

Analyst-dominant org chart

Public AI Commitment
84

Earnings-call AI mentions trending

Automatable Workflow Volume
81

Manual triage compressible

Transformation Readiness
85

Data + governance maturity present

Sector AI Velocity
83

Investor questions on AI per call

Evidence pack · 3

  • Open roles include Senior ML, Forward Deployed Engineer, AI PM. Hiring across NA + EMEA.

    fetched 6/15/2026 · dims: transformation_readiness, public_ai_commitment

  • AI named as a top-3 priority in latest investor communication.

    fetched 6/1/2026 · dims: sector_velocity, kw_density

  • Post details internal agent pilot, evaluation harness, and rollout cadence.

    fetched 5/27/2026 · dims: public_ai_commitment, sector_velocity

Re-run scoring for Capstone Construction