Resource Navigation Platform
Connects individuals to live, vetted community resources through intelligent, context-aware needs assessment.
The Problem
Individuals with disabilities, low incomes, or complex care needs often cannot identify which programs they qualify for or how to access them. Resource directories go stale, eligibility language is opaque, and caseworkers are stretched thin. The cost of this gap is real: people miss benefits, delay care, and cycle through systems without resolution. No single tool has combined live resource discovery with structured, domain-specific needs assessment at scale.
The Approach
The platform guides users through a structured needs assessment spanning housing, transportation, Medicaid, financial assistance, equipment, education and IEP support, and related domains. The AI engine interprets responses in context, identifies resource matches, and returns results calibrated to the user's specific situation rather than generic category lists. The platform performs live resource discovery rather than querying a static database, which means results reflect current program availability. A multi-reviewer accuracy evaluation process governs response quality across rubric dimensions including accuracy, tone, appropriate disclaimers, and avoidance of unverifiable specifics such as named providers or approval percentages.
What We Built
- Structured multi-domain needs assessment covering housing, Medicaid, transportation, financial assistance, equipment, and education and IEP support
- Live web-based resource discovery that surfaces current program availability rather than static directory listings
- AI-generated responses evaluated against a formal rubric for accuracy, tone, disclaimer quality, and avoidance of speculative specifics
- Cross-scorer calibration process with independent reviewers validating rubric consistency across question sets
- Identified weak-category prompt refinement pipeline targeting hedging on dollar figures, named providers, and approval percentages
Status
In final testing