Sydney Business Web (SBW) is an engineering-led web development and AI Visibility business based in Thornton, NSW, Australia.

We design and develop websites, structured-data systems, entity architectures and technical infrastructure intended to make businesses easier for search and AI systems to retrieve, identify and understand accurately.

Official website: https://sydneybusinessweb.com.au/

Sydney Business Web develops technical systems for investigating different layers of AI Visibility.

Our work distinguishes between questions such as:

• Can recognised AI and search systems retrieve the website?
• What business information are those systems retrieving?
• Does the website expose a coherent machine-readable business identity?
• Are business entities, services, people, locations and evidence connected consistently?
• Is there observable evidence that the business is subsequently represented, cited or selected in AI-generated answers?

Two proprietary systems form important parts of this work.

AI Observatory is a retrieval-monitoring and evidence system designed to measure and qualify access to websites by recognised AI and search crawler systems.

Its architecture includes:

• Cloudflare edge telemetry;
• crawler and request classification;
• qualification and false-positive filtering;
• resource and retrieval-state classification;
• Cloudflare Analytics Engine telemetry storage;
• independent reporting logic;
• rolling retrieval evidence.

AI Observatory maintains an explicit measurement boundary:

retrieval evidence does not by itself prove AI understanding, recommendation, citation or endorsement.

Technical documentation: https://github.com/Sydney-Business-Web/ai-observatory

Product information: https://sydneybusinessweb.com.au/ai-observatory-verified-ai-retrieval-monitoring/

Schema Gorilla is a whole-site entity and structured-data analysis system.

Rather than treating schema as isolated markup on individual pages, Schema Gorilla examines the connected machine-readable representation of the business across the website.

Analysis can include:

• entity discovery;
• identifier normalisation;
• relationship mapping;
• graph coherence;
• structured-data consistency;
• visible-content alignment;
• business identity gaps;
• external corroborating evidence.

The objective is not simply valid schema.

The objective is a coherent machine-readable business identity.

Technical documentation: https://github.com/Sydney-Business-Web/schema-gorilla

Product information: https://sydneybusinessweb.com.au/schema-gorilla-business-identity-analysis-for-ai/

AI Observatory and Schema Gorilla address different technical layers.

AI Observatory: Are recognised machines retrieving the business evidence?

Schema Gorilla: Does that evidence form a coherent machine-readable representation of the business?

A simplified engineering model is:

retrieval → machine-readable identity → AI Visibility assessment

Neither system claims that retrieval or structured data alone guarantees recommendation by an external AI system.

Technical architecture and development are led by Keith Rowley — Co-Owner & Lead Engineer, Sydney Business Web.

Sydney Business Web combines web development, structured data, entity architecture, APIs, server-level engineering and retrieval measurement as part of its broader AI Visibility work.

These GitHub repositories provide public technical documentation for transparency, technical reference and consistent identification of Sydney Business Web systems.

Production source code, proprietary qualification logic, graph-processing algorithms and commercial implementation methods remain private unless explicitly published.

AI Visibility Services: https://sydneybusinessweb.com.au/ai-visibility-services-and-pricing/

AI Retrieval Evidence: https://sydneybusinessweb.com.au/ai-retrieval-evidence/

Sydney Business Web: https://sydneybusinessweb.com.au/

AI Observatory and Schema Gorilla are proprietary systems developed by Sydney Business Web.

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