Runs

Inspect · scoring run

Brightline Public Schools · b4f51bf1

model · google/gemini-2.5-prosegment · industriesconfidence · lowevidence · 3latency · 3.17 sat · 6/16/2026, 10:00:00 PM

Account

Brightline Public Schools

Public Sector / Ed · tier Hold

Overall

42

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": "Watch",
  "notes": "",
  "company": "<see accounts.name>",
  "overall": 54,
  "segment": "industries",
  "why_now": {
    "date": "2026-05-24",
    "type": "funding",
    "label": "Series C closed; AI named in use of proceeds",
    "detail": "Captured from public sources during nightly pass.",
    "source_url": "https://example.com/whynow/f1caff11",
    "source_type": "press"
  },
  "industry": "",
  "use_case": "",
  "comparable": "",
  "confidence": "low",
  "dimensions": [
    {
      "key": "kw_density",
      "name": "Knowledge-Worker Density",
      "score": 57,
      "rationale": "Analyst-dominant org chart",
      "evidence_refs": [
        1
      ]
    },
    {
      "key": "public_ai_commitment",
      "name": "Public AI Commitment",
      "score": 48,
      "rationale": "Earnings-call AI mentions trending",
      "evidence_refs": [
        3
      ]
    },
    {
      "key": "workflow_volume",
      "name": "Automatable Workflow Volume",
      "score": 56,
      "rationale": "Backlog of structured drafting work",
      "evidence_refs": [
        1
      ]
    },
    {
      "key": "transformation_readiness",
      "name": "Transformation Readiness",
      "score": 54,
      "rationale": "Data + governance maturity present",
      "evidence_refs": [
        1
      ]
    },
    {
      "key": "sector_velocity",
      "name": "Sector AI Velocity",
      "score": 48,
      "rationale": "Competitive pressure rising",
      "evidence_refs": [
        2
      ]
    }
  ]
}

Parse · five dimensions

Knowledge-Worker Density
44

Records and admin work is dense

Public AI Commitment
28

No AI roles on careers page

Automatable Workflow Volume
52

Procurement constrained

Transformation Readiness
46

Records office whitespace

Sector AI Velocity
40

Public sector slow on AI

Evidence pack · 3

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

    fetched 6/15/2026 · dims: sector_velocity, workflow_volume

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

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

  • New executive role created to own AI strategy across business units.

    fetched 5/28/2026 · dims: sector_velocity, kw_density

Re-run scoring for Brightline Public Schools