An RN initiative · in development

Aloha AI

AI-specific education, decision support, tools and implementation work, held within RN’s practice. The organising claim is narrow: most organisations adopting AI do not have a technology problem, they have a decision-architecture problem, and the work that would have made the decision good happens before any vendor is chosen.

The problem it works on

The missing step is not technical.

Organisations are routinely pushed from a vague intention to use AI straight into vendor selection. What gets skipped is the part that determines whether the result is any good.

Defining the bounded problem. Considering the non-AI alternatives honestly. Identifying who is affected and asking them. Preserving the evidence and the uncertainty rather than the conclusion. Assigning ownership to a person, not a committee. And deciding in advance — while it is still cheap to decide — what would make a pilot stop, and what rolling it back would involve.

Every tool under this initiative is an attempt to make one of those steps cheap enough that a team actually takes it. They are browser-local by design: no account, nothing transmitted, and each one states the judgement it cannot make on your behalf.

11 builds · verified reachable

What exists under Aloha AI right now.

Each of these was checked and answered at the last regeneration of the build index. Two are prototypes and one is a proposal; they are labelled as such rather than folded into the same present tense as the released tools.

Aloha AI

LiveLive · practice platform, active development

Carries the public service catalogue, learning products including a twelve-issue Decision Desk and a citation verifier, machine-readable catalogue and feed routes, an offline recovery shell, and four browser-local decision aids: the Opportunity Studio at /studio, which walks twenty-three steps to map the work before any tool is chosen, and three at /tools — a decision record that preserves alternatives, owner, uncertainty, stop conditions and review triggers; a vendor comparison that tests the current process and two candidates against five non-negotiable gates plus your own weighted criteria; and a pilot designer covering hypothesis, baseline, measures, authority, affected-party input, stop and rollback.

Open the build Case study

AI Build Cost Workbench

LiveLive · v2, August 2026

Walks six stages — project brief, editable labour architecture across eight workstreams, model and API workloads, infrastructure, one-time and recurring costs, named uncertainty drivers — and returns cost composition, sensitivity drivers, build and monthly ranges, and a first-year total. Scenarios save locally, share by URL, print to PDF, and export as CSV and JSON. The model-price catalogue is dated and editable rather than hidden behind a project-type selector.

Open the build Case study

Campaign Governance Issue-Spotter

LiveLive

Runs a browser-local checklist over a cultural or AI-enabled campaign, linking each question to its official source and stating where the checklist stops.

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Creator Rights Issue Spotter

LiveLive

Asks seven questions and returns the issue areas they implicate across creator rights, AI use, disclosure, likeness, music, jurisdiction and platform review.

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The Third Asset

LiveLive

A browser-local workbench for mapping synthetic-media, creator-rights, disclosure, provenance and incident-response decisions before they are needed, so the incident plan exists in advance of the incident.

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AI Governance Tracker

LiveLive · weekly automated collection · last sweep current

Runs a scheduled sweep every Monday, files what it finds into those five categories, and publishes the result as a dashboard and a JSON endpoint. The API returns a collection-health block alongside the documents: last sweep time, age in days, failed-search count, newest item date, and a stale flag that trips after two missed cycles. A stale register is shown as stale rather than presented as the current picture.

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Culture Intelligence Monitor

PrototypePrototype · exploratory, not on a maintained sweep schedule

Tracks film, television and cultural moments alongside consumer style and spending signals, and attaches an AI governance risk score to each read so the inference and its reliability travel together rather than the score arriving alone.

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Behavioral Intelligence Layer

PrototypePrototype · thin by design, and thin in practice

Turns a screen-culture attention signal into an explicitly testable consumer-behaviour hypothesis, and states a use boundary on the same page.

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The Encoding Effect

PrototypePrototype · interactive research note

Sets out a sourced hypothesis about how screen worlds may become self-relevant, presented as an interactive research note with an evidence ledger attached and its limits stated in the body rather than in a footnote.

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Aloha Build Club

LiveLive · daily room

Runs a daily body-doubling room for people building with AI — show up, build alongside others, leave with something shipped.

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The Sovereign Stack

ProposalProposal · independently initiated, not adopted

Demonstrates a possible decision protocol, a living system record, a bounded pilot path and an optional learning translation, organised around the governance questions a community-authorised process would still have to answer.

Open the build Case study

Statuses come from the generated inventory behind the complete build index, not from this page, so an initiative page cannot describe more than is actually deployed.

Current boundary

The platform is substantial.
Its products have separate completion gates.

The public platform contains learning surfaces, evidence, decision tools and service pathways. A masterclass, a twelve-month plan, a Decision Desk issue, a Source Desk surface or a Clinic is not complete merely because a page or an architecture for it exists, and this initiative does not treat the existence of a route as the existence of a product.

What the live platform does establish: a routed starting experience, open learning and Source Desk surfaces, procurement and accessibility pathways, and four complete browser-local decision aids — the Opportunity Studio, and a decision record, a vendor comparison and a pilot designer under its tools route. What it does not establish: completed client engagements, independently verified source accuracy, enterprise collaboration, professional advice, compliance certification, or improved organisational outcomes.

Read the verified case study →Open the current platform ↗

Relationship to NSAG

Two initiatives, one of which builds for the other.

Aloha AI is the client-facing strategy and build practice. The Neurocognitive Systems Advisory Group is the research-led institutional-design practice. They are separate, and the separation matters: Aloha AI may build technical infrastructure that implements NSAG work, but an Aloha AI tool is not an NSAG finding, and neither initiative inherits the other’s evidence.

See the NSAG initiative →