Editorial Policy & Empirical Research Standards
How Infinitus sources, verifies, tests, and publishes technical intelligence on AI discovery, search engine optimization, answer engine optimization, and generative retrieval for Singapore and Southeast Asian enterprises.
Infinitus publishes research, technical playbooks, and strategic guides grounded in empirical testing and verifiable primary sources. We strictly prohibit unverified ranking guarantees, undisclosed commercial bias, and unsubstantiated claims. All published analyses undergo human review by our founding partners, Benjamin Tay and Zachary Tay, under the seven core standards outlined below.
Empirical Independence & Research-First Mandate
Our research mandate is to provide clear, actionable, and mathematically sound visibility intelligence for commercial enterprises in Singapore and Southeast Asia. We maintain absolute editorial independence:
- Zero Paid Inclusion: We do not accept payment, sponsorship, or affiliate fees to feature, rank, or review any platform, vendor, or tool.
- Objective Benchmarks: In our Singapore Digital & AI Visibility Benchmarks, scoring is strictly determined by documented technical criteria, not commercial relationships.
- Client Telemetry Firewalls: Consulting clients receive tailored strategic roadmaps, but client participation does not alter our published public research or sector indices.
Hierarchical Data Sourcing Architecture
Every empirical claim, statistic, and recommendation published on Infinitus must map directly to our 4-tier sourcing hierarchy:
Internal telemetry from the Infinitus Discovery Lab, multi-engine citation test executions (N=60+), and crawler log analysis.
W3C Web Standards, Schema.org official vocabularies, IETF RFC 9309 (Robots Exclusion Protocol), Google Search Central, and OpenAI/Anthropic/Perplexity documentation.
Published observational studies from BrightEdge, Authoritas, SparkToro, Ahrefs, Semrush, and peer-reviewed academic AI research.
Ministry of Health (MOH), Health Sciences Authority (HSA), Singapore Medical Council (SMC), Singapore Dental Council (SDC), Enterprise Singapore, and ACRA.
Claim Discipline & Anti-Hype Guarantee
The AI marketing landscape is saturated with unsubstantiated promises. Infinitus enforces strict claim discipline across all publications:
AI outputs are stochastic and non-deterministic. Recommendation and citation weights vary continuously based on model version, query context, geographic geolocation, and conversational state. No agency, tool, or software can guarantee that ChatGPT, Perplexity, Gemini, or Google AI Overviews will cite or recommend a specific business.
We explicitly differentiate between controllable engineering factors (crawler accessibility, JSON-LD Schema completeness, entity disambiguation, answer-first formatting) and uncontrollable external model behavior.
First-Party Empirical Testing & Replication Protocols
Whenever Infinitus publishes data from our Discovery Lab, the study includes full disclosure of the testing protocol to ensure scientific rigor and replication readiness:
Corrections & Transparent Errata Protocol
In the fast-moving AI landscape, technical specifications and search engine documentation evolve frequently. When corrections or updates are warranted:
- Timestamped Updates: All updated articles include a clear
dateModifiedheader explaining what technical parameters were updated. - Factual Correction Notes: Substantive factual errors are corrected inline with an explicit errata notice at the bottom of the article.
AI Assistance Disclosure & Human Expert Mandate
We believe transparency in AI usage is foundational to digital trust:
- Permitted AI Assistance: We utilize specialized software and LLM tools for static syntax linting, data clustering, multi-query execution, and code formatting.
- Human Authorship & Accountability: No published guide, benchmark, or playbook is generated autonomously. All strategic insights, regulatory interpretations, and technical recommendations are authored, validated, and signed off by qualified human specialists.
- Hallucination Defense: Every citation, quote, statistical figure, and external URL is manually checked against authoritative source documentation prior to publication.
Commercial Independence & Client Confidentiality
We protect our clients' proprietary data while maintaining strict separation between consulting services and public intelligence:
- Strict Anonymization: Case studies and aggregate dataset benchmarks never disclose non-public client revenue, internal conversion metrics, or proprietary system architectures without explicit written consent.
- No Pay-to-Play Rankings: Commercial engagements never guarantee preferential placement or biased review outcomes in our public benchmarks.
Benjamin Tay
Specializes in Generative Engine Optimization (GEO), commercial search strategy, and digital visibility for Singapore and Southeast Asian enterprises. Focuses on aligning technical AI readiness with measurable commercial outcomes.
Zachary Tay
Specializes in software architecture, knowledge graph engineering, Schema.org infrastructure, and Next.js systems. Leads technical research at the Infinitus AI Discovery Lab.
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