Intelligent Partnerships
Partnership proposals are not templates. They emerge from the convergence of all four units of analysis — students, courses, occupations, and employers — queried simultaneously against a unified knowledge graph.
The Convergence
Each proposal draws on employer metadata, regional occupation demand, aligned curriculum, and student pipeline data. The system queries across all four simultaneously, ensuring that every claim in the proposal is grounded in evidence from the graph.
The Pipeline
Graph queries retrieve the full context for a partnership: employer metadata, the occupations it hires for, regional demand evidence, curriculum aligned to core skills, and the student pipeline with matching competency profiles.
Employer name, college identity, engagement type
Employer context, occupation evidence, curriculum alignment, student pipeline data
LLM-based intelligence applies domain judgment to the gathered context. It selects the primary occupation, identifies the core skills, narrows to the most relevant departments, and — for curriculum co-design — identifies one gap skill the curriculum does not yet develop.
Full gathered context from Stage 1
Selected occupation, core skills, relevant departments, gap skill (if applicable)
Claude generates proposal prose constrained to evidence from the gather stage. The narrative cannot hallucinate — it can only reference data that was retrieved from the graph. A post-generation faithfulness check verifies that every claim is supported.
Filtered context with selected occupation and core skills
Four-section proposal: opportunity, curriculum alignment, student pipeline, roadmap
The Proposal
Every proposal follows the same structure: an opportunity grounded in labor market evidence, curriculum alignment verified against institutional course records, a student pipeline quantified from enrollment data, and a concrete roadmap. Narrative prose is always accompanied by its underlying evidence.
Wages, openings, and growth rates from Centers of Excellence regional data
Course records from the college's own catalog, parsed and skill-mapped
Enrollment counts and competency profiles calibrated to DataMart
Pacific Regional Medical Center operates a 312-bed acute care facility with documented nursing shortages across emergency, surgical, and ambulatory care units. Regional demand for registered nurses projects 2,400 annual openings at a median wage of $128,400, with a five-year growth rate of 8.2%. The facility's proximity to campus and existing clinical site agreements position it as a high-alignment internship partner.
The Nursing Sciences department offers a 14-course registered nursing pathway that develops 5 of 6 core skills identified for this partnership. Clinical Assessment and Patient Care are developed across multiple courses with dedicated lab components. Electronic Health Records proficiency is embedded in the Health Information Technology sequence.
The aligned nursing and health information technology programs enroll 284 students, of whom 47 demonstrate proficiency in all 6 core skills. The top candidates combine clinical coursework with health records training, producing a competency profile that matches the facility's integrated care model.
Begin with a 6-week summer clinical rotation for 8-12 students in emergency and ambulatory care. Map clinical hours to NURS 290 (Clinical Practicum) for academic credit. Establish a preceptor matching process with unit charge nurses. Target first cohort for Summer 2026 with an evaluation checkpoint at week 4 to assess patient interaction competency and EHR documentation readiness.
Three Engagement Types
Structured on-site work experience connecting students to real workplace environments. The standard pipeline: gather employer context, select a primary occupation, identify relevant curriculum and students, generate a placement-ready proposal.
Direct path from skill alignment to workplace placement.
Employer shapes program content by identifying curriculum gaps. Extends the standard pipeline with a gap skill identification step — the system finds one skill the employer needs that the curriculum does not yet develop, and proposes how to close it.
Adds gap skill identification and remediation strategy.
Ongoing strategic guidance from industry into institutional planning. Selects multiple identity-defining occupations, synthesizes an advisory thesis explaining why the employer's perspective matters, and generates inaugural board agenda topics.
Multi-occupation selection, thesis synthesis, and agenda generation.
Strong Workforce
A discovered partnership is not an endpoint — it is feedstock for institutional action. The same occupation evidence, curriculum alignment, and student pipeline data that justifies a partnership also supplies the labor market information context required for a NOVA-compatible Strong Workforce Program application. The proposal becomes a fundable project.