Keaton Taliaferro · AI tools for nonprofits
Not chatbot wrappers — verifiable tools. Every project backs its output with something a human can confirm in seconds: a verbatim citation, a rubric you can read, a signal you can trace.
Why it matters: the easy version of "AI for nonprofits" is a thin wrapper around an agreeable model. In a domain where a wrong "yes" costs an organization a grant or ships a broken laptop to a family, agreeable-and-confident is dangerous. So I separate the model from the decision — the model observes, deterministic code you can audit decides.
Turns a funder's RFP into a checklist of every requirement, then checks your draft against all of them.
Extracts each requirement with a verbatim RFP citation, and refuses to mark anything "met" unless it can quote your own draft back — catching the model fabricating coverage, live.
A ~$21 edge sensor that predicts a failing food-bank fridge hours early — with zero AI at runtime.
Predicts failure from the warming trend, ignores door-opens so the alarm stays trusted, and alerts offline — enforced by a source-level test. Same logic ships in browser JS and ESP32 firmware.
Consistent, standards-based grading for donated computers, so a good machine isn't scrapped and a broken one isn't shipped — my signature project, applying industrial quality-inspection discipline to e-waste.
The vision model only observes; a versioned rubric with severity floors decides — and no blocking-defect device can ever be graded "refurbish," enforced against the model and a human override.
100% client-side. No servers, no telemetry, no API keys. In "live" mode the only network call is to a model on your own machine (local Ollama).
Verification is plain, inspectable code. No AI is required to check the AI — each safety engine is a few hundred readable lines with automated tests.
Runs free, forever, on hardware you own. Nothing to subscribe to; deployable by a nonprofit at $0/month.
Data-safe by design. Demos use public or synthetic data only — no client's confidential material anywhere.