I build practical artificial intelligence tools for foundations and nonprofits, with a focus on funder discovery, grant strategy, proposal review, and due diligence. My mom has dementia, so my digital health tools support care decisions, cognitive-screening workflows, and healthcare strategy.

This portfolio is evidence for the Built By User idea: people close to a problem can turn their judgment into a working prototype, test the useful part quickly, and make the method easier to inspect through public code, source links, and explicit human-review boundaries.

Many of these tools are open for inspection in my public GitHub repositories. The code is not a claim that every prototype is production-ready. It is a record of how each tool works, what assumptions it makes, and where human judgment still belongs.

Foundation and Nonprofit Tools

• Funder Discovery
  Helps nonprofit teams discover possible funders, score fit against an organization profile, review public evidence, and avoid prospects that look attractive in a raw search but weak in practice. Source code.
• Funder Finder
  Turns a focus area or proposal draft into linked federal and foundation opportunities with cited fit signals. It is meant for a first prospecting pass, when the question is where staff time merits deeper research. Source code.
• Grant Fit Auditor
  Reviews a grant opportunity against a nonprofit profile, extracts requirements, ranks gaps, and recommends whether to pursue, pause, or decline. Its value rests on helping teams reject bad-fit opportunities before writing begins. Source code.
• Grant Decider
  A static companion implementation of the grant pursuit decision interface. It gives nonprofit teams a first-pass pursue, pause, or decline decision before staff invest in an application. Source code.
• Grant Analyst
  Performs evidence-first pre-submission review of eligibility, proposal merit, funder fit, evidence quality, and competitive readiness. It does not predict whether a proposal will receive funding. Source code.
• Foundation Grant Signal Lab
  Turns a proposal, applicant profile, and foundation strategy into a first-pass decision memo with visible evidence, review routes, funder risks, and next diligence questions. Source code.
• Grant Guardian Financial Analyzer
  Reviews nonprofit financial risk signals so finance, program, and fundraising teams can ask sharper questions before a grant advances. It is a due-diligence aid, not an automated approval system.
• Funder Discovery Plugin
  A Codex plugin and Custom GPT Actions pilot for nonprofit funder discovery, fit scoring, 990-backed funder briefs, donor briefs, and CRM-ready pipeline exports.
• Funding Fit Scorer Template
  A customizable, staff-only application template for scoring funding opportunities against an organization strategy and producing a reviewable go or no-go memo.
• Proposal Compliance Checker
  Compares a proposal draft with a solicitation and flags missing, non-compliant, and human-review items before submission. It checks completeness and compliance, not proposal quality or funding probability. Source code.
• Claude Skills Creator
  Helps teams turn repeatable expertise into structured AI workflows for grant research, compliance review, credibility checks, and funder-specific writing. Source code.
• Kindora for ChatGPT MCP
  A read-only Python MCP server that exposes Kindora public funder and grant tools inside ChatGPT for grant discovery workflows.
• NGO Executive OS
  An experimental AI executive-assistant starter kit for NGO fundraising and strategy, organized as reusable workflows rather than a single public application.
• GEO Audit Studio
  Creates an AI-search audit prompt, scorecard, measurement plan, and action pack so website owners can test whether AI systems can access, understand, cite, and accurately describe a site. Source code.
• NIH Subaward Checker
  Turns a specific NIH prior-approval notice into a practical grants-office check for domestic subaward changes. Deterministic policy logic remains separate from AI-assisted extraction and drafting. Source code.

Digital Health and Caregiver Tools

• First Signs Health
  Turns published cognitive-screening protocols into a family-usable browser workflow and a clinician-ready handoff document. It does not diagnose.
• Dementia Care and CCM Billing Guide
  Translates dementia-care and chronic-care-management billing choices into a practical decision aid for clinicians, caregivers, and families.
• Cognitive Screening Tool
  Combines clock-drawing and cognitive-screening workflows in a browser interface while leaving medical interpretation and follow-up with a clinician.
• Cog-Free Dementia Risk Estimator
  Explores a non-diagnostic risk-estimation workflow designed to help a user decide whether a clinical conversation merits attention.

How I Build

Built By User is my build philosophy. A domain expert can test the useful core of an idea before committing to a long procurement or development cycle, then bring in engineering, security, legal, or clinical judgment where the work becomes sensitive or consequential.

I start with a concrete decision that doesn’t waste time or money: which funder to pursue, whether a proposal merits staff effort, what a compliance notice requires, which contract clause may apply, or what evidence should reach a clinician. I build the smallest useful tool around that decision, keep source material visible, and separate prototype value from production readiness.

Public code is part of the accountability model. It makes methods inspectable, limitations easier to find, and future changes easier to evaluate. Review the complete repository list at github.com/wayanvota.