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Demo mode Microsoft Global Hackathon 2026 · Browser-local sample data · Production records are protected

Hack for Good with a Nonprofit

Preserve the past. Empower today’s storytellers.

See how one small museum can deliver an accessible visitor experience and manage its own history, events, media, and daily work without permanent technical dependency.

2 minguided judge path
0logins required
3AI-assisted workflows
100%human publication control

Judge-ready path

Four stops. One sustainable operating model.

Use these stops in order for a concise demonstration, or open any area to explore independently.

Start with the story

Watch RailKeeper come to life.

This short film follows the visitor experience, protected staff work, and human decisions that let a small museum preserve history without surrendering authority.

Playback is always your choice. The film never starts automatically, and English captions are available from the player.

RailKeeper AI · Human-governed community heritage operations
1

Begin with the visitor

Show accessible history, oral histories, tours, family learning, and a virtual Photo Booth built for different ages and abilities.

2

Transfer capability

Move behind the scenes to a museum-language dashboard: events, schedules, stories, photographs, visitor activity, and recovery.

3

Reduce administrative effort

Turn an existing announcement into a structured event draft and route “Where do I change…?” questions to the right task.

The design thesis

The best technology eventually gets out of the institution’s way.

RailKeeper AI does not ask a small museum to become a software company. It translates museum work into understandable tasks, preserves human authority over history, and leaves behind an operating capability—not a permanent dependency.

Responsible AI in practice

Human-governed agentic engineering.

Observe → gather evidence → prepare → review → approve → publish → learn. The workflow coordinates work while museum staff retain every consequential decision.

Demonstrated

People remain accountable

AI prepares suggestions. Museum staff verify sources, consent, context, accessibility, and the final publication decision.

Designed for choice

No single-model dependency

The AI service boundary supports Azure OpenAI or OpenAI, remains dormant when unconfigured, and leaves the museum’s records in provider-neutral formats.

Governed operations

Observe access and change

Role gates, audit records, source labels, privacy-preserving visitor signals, deployment checks, and recovery points make operation reviewable.

Community outcome

Capability stays in Princeton

Accessible visitor tools and museum-language staff workflows help a local institution operate without permanent technical dependency.

Honest boundary: this page uses deterministic browser-local examples. Production AI usage and cost telemetry should remain a visible operational control before broader AI activation.

For visitorsHistory they can hear, explore, and participate in.
For staffPlain-language tools that match the work they already know.
For the institutionA sustainable handoff with safeguards, documentation, and recovery.

Safety boundary: this showcase never signs in as museum staff and never calls a write API. Every simulated change stays on this page until Reset.