Why it matters

Three people in a café. One says 'Modern AI models are trained on the internet'. Another corrects them: 'They are actually trained on carefully filtered high-signal subsets of the internet plus curated datasets!' The third replies: 'Well, I need to optimise my content for AI ingestion then.'
A cartoon character looks at a pile of low-signal content and a highlighted AI Knowledge Signal logo card labelled high-signal content. Caption: 'Companies that win in the Age of AI build authority and trust — for machines and humans.'

Most organisations assume AI systems train on "the internet." They do not. Modern large language models are trained on carefully filtered, high-signal subsets of the web — plus curated datasets selected for quality, authority, and epistemic reliability. Content that doesn't meet those standards doesn't make it in.

AI Knowledge Signal exists to close that gap: to give organisations a practical framework for publishing knowledge that survives quality filters, earns citations, and builds authoritative representation inside AI systems.

Our mission

Mission statement

To help organisations publish knowledge that machines understand, trust, and cite — so that when AI systems answer questions about a market, a problem, or a category, the right voice is in the room.

AI Knowledge Signal is a product of Digital Human Assistants, a research and product studio focused on the intersection of human knowledge, AI training pipelines, and generative engine optimisation.

Founder

Christopher Foster-McBride, founder of AI Knowledge Signal

Christopher Foster-McBride is the founder of AI Knowledge Signal and Digital Human Assistants.

Christopher originated the concept of the AI Trust Paradox (Verisimilitude Paradox) — A counterintuitive reality which describes that as LLMs / MFMs improve, their outputs become increasingly indistinguishable from human-generated text and users may assume that a well-articulated response is inherently accurate, overlooking the possibility of errors lurking beneath the polished surface. This misplaced trust can lead to the propagation of misinformation, flawed decision-making, and erosion of critical thinking skills.

In 2022, Christopher founded TokensCompare, the first dedicated platform for discussing LLM architectures (with a focus on tokenisation) and trends related to commercial proprietary models, pricing models, and the open-source community.

If you would like to learn more and discuss guidance implementing the framework or bespoke AI-related consulting services, book now.

Resources

Free resources from AI Knowledge Signal to help your organisation understand and act on the AI knowledge opportunity.

How to cite this work When referencing the AI Knowledge Signal framework (2026), please cite: Foster-McBride, C. (2026), AI Knowledge Signal Framework, Digital Human Assistants, accessed at aiknowledgesignal.io.