What is inspectable now, and what needs your data.

What does Blue Ninja measure before anything is generated?

The diagnostic report shape separates measured crawl/support checks from recommendations, fit notes, and next actions.

Boundary: The public report is a sample shape; customer scores and recommendations depend on the live site crawl and submitted context.

Next validation: Run a diagnostic for the customer's real domain and archive the report before build work starts.

Can a buyer inspect the product flow before purchase?

The public demo walks from intake and diagnostic proof to support publishing, changelog review, and monitoring boundaries.

Boundary: The journey uses safe sample data and does not represent a customer case study or production outcome claim.

Next validation: Replace sample-only proof with approved customer screenshots and case studies when available.

What does the published customer-facing support system look like?

The sample support center exposes hubs, answers, search paths, feedback controls, metadata, and crawlable public URLs.

Boundary: A real support center becomes proof only after owner approval, publish verification, and production visual smoke pass.

Next validation: Verify a seeded published support slug on production after the confirmed Vercel project serves current main.

Can owners and customers see what changed after launch?

The public changelog shows live and archived snapshots, artifact counts, hub coverage, verification state, and version links.

Boundary: Sample versions prove the review surface; customer-specific claims require approved published snapshots.

Next validation: Add a seeded customer-safe support slug to CI smoke when fixture data is approved.

How does the system prevent unsupported answers from going live?

Authenticated approvals include quality gates, unsupported high-risk claim blocking, source maps, live-vs-proposed diffing, and audited admin override controls.

Boundary: This is not public without a seeded authenticated account; release proof still needs app screenshots from staging or production.

Next validation: Capture seeded authenticated approval-list and approval-detail screenshots after storage-state is available.

How are revenue, support, and AI-answer outcomes separated from weak signals?

Customer outcome reports separate proof-grade, directional, and unattributed revenue; support QA; feedback; deflection modeling; LLM Presence; and monitor actions.

Boundary: Outcome reports need real tracking, order, support feedback, and helpdesk-baseline data before public outcome claims are defensible.

Next validation: Connect tracking/orders/helpdesk baselines for each customer and review monthly report snapshots before quoting results.

Can revenue claims be tied to the support-and-answer system?

RevenueLoop labels direct and assisted rows as proof-grade, inferred rows as directional, and unknown rows as unattributed.

Boundary: Revenue movement should not be marketed as proof until first-party tracking and order data are connected and reviewed.

Next validation: Install tracking, connect Stripe or Shopify order ingestion, and confirm attribution rows in the customer report.

What happens after publishing?

Monitoring surfaces convert provider status, prompt results, answer drift, citation gaps, and score drops into severity-ranked actions.

Boundary: Prompt visibility is measured for configured providers and prompt sets only; it is not a proprietary ChatGPT ranking tracker.

Next validation: Run customer-owned prompt sets, tune thresholds from real runs, and export monthly monitor actions.