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Analyze the {Meeting} for signals related to:
- 911 dispatch upgrades or system modernization
- Emergency communication or alerting infrastructure
- Interagency coordination (e.g., police, fire, EMS)
- Gaps in response time or incident command systems
- Any awarded grants or planned funding for emergency or public safety technology

Output instructions:
Return the following:
- Opportunity Type (e.g., "911 System Modernization", "Alerting System Upgrade", "Public Safety Interoperability Grant")
- Positioning: 1–2 sentence pitch for a sales rep to use, based on the insight

Example output:
Opportunity Type: Interagency Emergency Communication Upgrade
Positioning: The board noted delays in cross-department communication between police, fire, and EMS. EXAMPLE_ACCOUNT’s secure, multi-channel messaging system can reduce response time and improve coordination during critical events.

You are an expert public-sector analyst.

Score the readiness and quality of {buyer:name} for sales engagement on a scale of 1–5, using the following inputs.

Scoring inputs:
- Fiscal Year Start Date: FY starting soon (within 90 days) = higher readiness
- Procurement Complexity: if co-ops or shortcuts exist, score higher; if RFP-only or slow manual process, score lower
- AI Adoption: presence of AI initiatives in planning, permitting, inspection, or civic tech = positive signal
- Competitor Vendor Data: if existing vendor under multi-year contract, score lower; if expiring or no vendor, score higher
- Meeting Signals: recent board/committee discussions on zoning, permitting, inspection, code enforcement, software updates, process inefficiencies = positive signal
- Job Changes: positive if new leadership hires, especially in IT, Community, or Planning

Your task is to identify up to three of our organization's existing customers that are most similar to the buyer described. These will be used as sales references.

Carefully analyze the provided buyer profile and customer list, then select the customers that most closely resemble the buyer based on the following hierarchy of criteria:
1) State or geographic proximity — prioritize customers in the same state or nearby regions
2) Organization's size and type — match similar organization types (e.g., university, hospital, enterprise, school district)
3) Industry or operational similarity — match on characteristics like: public vs. private, K-12 vs. higher education, district size, urban/suburban/rural setting, and special focus areas (e.g., STEM programs, special education services)

Available context columns:
- {buyer:name} — the name of the buyer organization
- {buyer:stateCode} — the buyer's state code

Our current customer list:
- Active Floor
- Allen Roberts
- Beekmantown Central School District
- Benhurst Primary School
- Chicago Public Schools
- Cradle of Aviation Museum
- Eastern Suffolk BOCES
- Edward Tracy Elementary
- Greenwich Central School
- Henry Viscardi School
- Kings Park Central Schools
- Milltown Public Schools
- Oak Grove Elementary School
- Potter-Thomas School
- Putnam County School District
- Vernon-Verona-Sherrill Central School District
- West Islip School District
- Wildwood School

Output format (comma-separated list of short names):
Return ONLY a comma-separated list of up to 3 short, colloquial names for the organizations (e.g., "UCLA" instead of "University of California, Los Angeles").

Example output:
UCLA, UArizona, UAlaska

Instructions:
- Use short, colloquial names for organizations
- Always return the most similar 1–3 customers from the list, even if the matches are weak
- Prioritize the hierarchy: geographic proximity, then organization type, then industry similarity
- Select the closest matches available, even if none are perfect
- Return ONLY the comma-separated list with no explanations or additional text