Runs

Inspect · scoring run

Tundra Cold-Chain · 177fa8cc

model · google/gemini-2.5-prosegment · industriesconfidence · highevidence · 3latency · 3.56 sat · 6/15/2026, 7:00:00 PM

Account

Tundra Cold-Chain

Cold-Chain · tier Priority

Overall

85

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": 85,
  "segment": "industries",
  "why_now": {
    "date": "2026-06-05",
    "type": "earnings_call",
    "label": "CEO emphasized agent-led ops on earnings",
    "detail": "Captured from public sources during nightly pass.",
    "source_url": "https://example.com/whynow/9edecfa8",
    "source_type": "press"
  },
  "industry": "",
  "use_case": "",
  "comparable": "",
  "confidence": "high",
  "dimensions": [
    {
      "key": "kw_density",
      "name": "Knowledge-Worker Density",
      "score": 90,
      "rationale": "Reading/writing heavy workforce",
      "evidence_refs": [
        1
      ]
    },
    {
      "key": "public_ai_commitment",
      "name": "Public AI Commitment",
      "score": 80,
      "rationale": "Press release on AI program",
      "evidence_refs": [
        1
      ]
    },
    {
      "key": "workflow_volume",
      "name": "Automatable Workflow Volume",
      "score": 93,
      "rationale": "Manual triage compressible",
      "evidence_refs": [
        3
      ]
    },
    {
      "key": "transformation_readiness",
      "name": "Transformation Readiness",
      "score": 84,
      "rationale": "Recent platform consolidation",
      "evidence_refs": [
        2
      ]
    },
    {
      "key": "sector_velocity",
      "name": "Sector AI Velocity",
      "score": 89,
      "rationale": "Competitive pressure rising",
      "evidence_refs": [
        3
      ]
    }
  ]
}

Parse · five dimensions

Knowledge-Worker Density
89

Analyst-dominant org chart

Public AI Commitment
77

Press release on AI program

Automatable Workflow Volume
86

Backlog of structured drafting work

Transformation Readiness
90

Active change-mgmt practice

Sector AI Velocity
84

Competitive pressure rising

Evidence pack · 3

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

    fetched 6/9/2026 · dims: workflow_volume, public_ai_commitment

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

    fetched 5/30/2026 · dims: kw_density, sector_velocity

  • Company announced a multi-year AI transformation program with executive sponsorship.

    fetched 5/27/2026 · dims: kw_density, transformation_readiness

Re-run scoring for Tundra Cold-Chain