What this page is

The public review model explaining how listings are classified, checked, and surfaced.

Who this is for

Readers who need the evidence standard before trusting the public surfaces.

Trust and methodology

How Hospitality AI Index reviews vendors.

Hospitality AI Index is a manual-first, workflow-first public intelligence surface. It is designed to explain where a product fits, what evidence is available, and where evidence is still missing. It is not a scoring engine.

Browse the indexRequest stack review

Review model

Workflow-first mapping

Listings are organised around operational work, so visitors can understand where a product fits inside the stack.

Manual-first review

The public surface is curated by human review rather than automated scoring or fully machine-generated ranking.

London and UK relevance

UK and London checks are used to keep the surface grounded in the market the project is validating first.

Integration evidence review

Integration notes, product documentation, and implementation signals are checked to avoid vague capability claims.

Trust labels

Mapped

The product has been placed into a workflow or operational cluster.

Profile Reviewed

The public profile has been checked against the canonical record and supporting source material.

Workflow Classified

The product has been grouped by the primary operational problem it serves.

UK Relevance Identified

The product is relevant to the UK market and, where useful, the London operating environment.

Integration Evidence Found

Public evidence exists for integrations, workflow fit, or implementation detail.

Vendor Submitted

The vendor has provided material that supports review or correction.

Operator Evidence Pending

Operator-side confirmation is still needed before stronger claims are made.

Verification Gap

There is not enough evidence to treat the listing as fully verified.

Why numeric scores are not used in Phase 1

Phase 1 is about trust visibility and operational clarity, not false precision. The page keeps the review model legible by showing what is known, what is inferred, and what still needs operator evidence before the index makes stronger claims.