Waldo pilot · Kansas City

Community AI for neighbor action.

NeighborhoodOS helps communities own AI capacity, share context, and solve real problems together. The first public step is education, training, & problem solving: a place to learn AI, bring stuck civic problems, and build small tools people can actually use.

Explore the pilot Open the Waldo dashboard
01

Education, training, & problem solving are the front door.

Learn

Practical AI literacy

Residents learn what AI can do, where it breaks, what private information to keep out of it, and how to check its work.

  • Plain-language sessions for beginners.
  • Scams, bias, privacy, and hallucinations.
  • Confidence for people most likely to be acted on by automated systems.
Solve

Bring a real problem

A stuck issue becomes a cleaner brief, a source list, a map of who is involved, and a next move a human can make.

  • 311 follow-up and city process puzzles.
  • Home repair, resource navigation, and paperwork snarls.
  • Neighborhood association bottlenecks.
Build

Make small useful tools

When a need is clear, builders and residents make simple helpers: trackers, guides, forms, checklists, and local assistants with human review.

  • Guided build nights.
  • Visible artifacts, not slide decks.
  • Community benefit first.

The goal is not one more “Intro to AI” class. The goal is a ladder: safe user, local problem framer, tool builder, peer helper.

02

Three functions, kept clear.

Hardware / local AI infrastructure

Shared tools & resources

Shared devices, local AI infrastructure, trusted places, training, agreements, and practical tools give the neighborhood capacity without handing the keys to an outside platform.

Public data & memory

Federated governance and neighborhood assets

Public data, federated governance, neighborhood asset tracking, meeting notes, resource maps, commitments, and provenance stay readable for people and agents.

Education, training, & problem solving

Learn, solve, build

This is the human layer. Neighbors bring problems, learn the tool, check the machine, and turn messy situations into practical next steps.

03

Public data and neighborhood memory start with sources that can be checked.

Public-data spine

Use what can be checked

The first public-data seed should be boring in the best way: fetched, linked, labeled, and honest about freshness.

  • Kansas City 311 requests, permits, violations, dangerous buildings, zoning, budgets, vendor payments, council agendas, and votes.
  • County and state records where they affect Waldo.
  • Links back to the real source when parsing is incomplete.
Waldo resources

The neighborhood knows things too

Public data is only half the story. Neighborhood memory also needs the living map of local help and local knowledge.

  • Neighborhood associations, libraries, churches, schools, clinics, nonprofits, mutual aid, and trusted local businesses.
  • Meeting notes, recurring problems, and open commitments.
  • Resource maps for people who need help now.
View Waldo dashboard Read agent overview GitHub source
04

Waldo is the first pilot.

1
Three Learn sessions

Resident-first AI literacy with special attention to people most exposed to automated systems.

2
Two Solve clinics

Real problems from residents, neighborhood groups, and local organizations, worked into next moves.

3
Two Build sessions

Small tools from actual needs: guides, trackers, intake forms, and source maps.

4
One public-data and memory seed

311, civic sources, county/state links, and Waldo resource data gathered into a shared memory layer.

Partner with the pilot

Bring a place, a problem, or a room of neighbors.

NeighborhoodOS is looking for partners who want a practical 90-day pilot: teach useful AI, work real problems, seed shared public data and neighborhood memory, and learn what a community-governed model should become.

  • Host an education or training session.
  • Bring a problem to a Solve clinic.
  • Help map public sources and Waldo resources.
Talk about the pilot