Inspect · scoring run
Lattice Genomics · d4a12b91
model · google/gemini-2.5-prosegment · techconfidence · mediumevidence · 3latency · 3.73 sat · 6/16/2026, 2:00:00 PM
Account
Lattice Genomics
Bio AI · tier Build
Overall
72
Prompt
score-account-tech · v1
You are scoring a mid-market technology account against the Anthropic field rubric.
Score each of the five dimensions 0-100 with a one-line rationale that cites the evidence URL it relied on:
1. Agent Opportunity — surface area for agentic workflows (support, ops, research, code)
2. Internal Transformation — evidence the org is actively rewiring around AI internally
3. AI Commitment — leadership posture, AI hiring velocity, product bets
4. Whitespace vs. Existing Spend — room to grow beyond current Anthropic or LLM usage
5. Industry Fit & Velocity — sector alignment with Anthropic ICP and rate of change
Return JSON: { overall:int, tier:"Priority"|"Build"|"Watch"|"Park", confidence:"high"|"med"|"low", dimensions:[{key,name,score,rationale,evidence_url}], use_case:string, comparable:string, talk_track:string }.
Tier thresholds: 80+ Priority, 62-79 Build, 46-61 Watch, <46 Park. Confidence is "high" only when at least three dimensions cite live public evidence.Raw response
exactly what Claude returned
{
"tier": "Build",
"notes": "",
"company": "<see accounts.name>",
"overall": 72,
"segment": "tech",
"why_now": {
"date": "2026-05-30",
"type": "linkedin_post",
"label": "Exec posted on Claude-style agent stack",
"detail": "Captured from public sources during nightly pass.",
"source_url": "https://example.com/whynow/d5b693a1",
"source_type": "careers"
},
"industry": "",
"use_case": "",
"comparable": "",
"confidence": "medium",
"dimensions": [
{
"key": "agent_opp",
"name": "Agent Opportunity",
"score": 72,
"rationale": "Multi-step procedural work observable in product",
"evidence_refs": [
1
]
},
{
"key": "ai_commit",
"name": "AI Commitment",
"score": 75,
"rationale": "Recent exec hire + AI roles posted",
"evidence_refs": [
2
]
},
{
"key": "transform_ready",
"name": "Transformation Readiness",
"score": 71,
"rationale": "Change-mgmt office stood up",
"evidence_refs": [
3
]
},
{
"key": "whitespace",
"name": "Whitespace vs. Existing Spend",
"score": 67,
"rationale": "Open RFP signals fresh budget",
"evidence_refs": [
3
]
},
{
"key": "industry_fit",
"name": "Industry Fit & Velocity",
"score": 74,
"rationale": "Sector aligned with Anthropic ICP",
"evidence_refs": [
1
]
}
]
}Parse · five dimensions
Agent Opportunity79
Repetitive triage at scale
AI Commitment65
Recent exec hire + AI roles posted
Transformation Readiness77
Re-platformed core within 18 months
Whitespace vs. Existing Spend65
No incumbent LLM contract detected
Industry Fit & Velocity74
Sector aligned with Anthropic ICP
Evidence pack · 3
Company announced a multi-year AI transformation program with executive sponsorship.
fetched 6/14/2026 · dims: industry_fit, agent_opp
AI named as a top-3 priority in latest investor communication.
fetched 6/4/2026 · dims: agent_opp, whitespace
Post details internal agent pilot, evaluation harness, and rollout cadence.
fetched 6/3/2026 · dims: agent_opp, transform_ready