Technology / Knowledge Structures

Knowledge Structures

Your RAG pipeline finds the right documents. It cannot tell your AI which ones are still true.

We research how organisations should structure knowledge before it enters an AI system — and how that structure affects what the AI can reliably do with it.

RESEARCH

Active collaboration with MIT on knowledge ingestion and inference optimisation

The problem

Unstructured knowledge produces unreliable AI.

Most enterprise AI projects ingest documents as undifferentiated text. The AI retrieves whatever is most similar — regardless of whether it is current, verified, or relevant in the right way.

We treat knowledge structure as infrastructure. Before retrieval, before generation, before deployment.

Epistemic typing at ingestion

Every document chunk is classified by its epistemic role before storage. A hypothesis and a decision require different retrieval logic — conflating them degrades output quality.

Deterministic decay

Knowledge expires. We assign decay rates at ingestion based on content type and domain. Stale knowledge is flagged before it reaches retrieval, not after it produces a wrong answer.

Contradiction as a first-class signal

Most systems silently average conflicting information. We surface contradictions explicitly so the AI — and the human — can reason about them rather than ignore them.

Inference optimisation

We research how the structure of ingested knowledge affects inference speed and accuracy. Better structure means faster, more precise answers at lower cost.

Taxonomy

Nine epistemic types

We classify every knowledge unit at ingestion. Each type carries different retrieval weight, decay rate, and contradiction sensitivity.

Decision

A resolved choice with documented rationale

Evidence

Verified data that supports or refutes a claim

Hypothesis

An untested proposition under investigation

Observation

A recorded fact without causal interpretation

Open Question

A problem without a current answer

Contradiction

Two pieces of information in conflict

Assumption

A premise accepted without verification

Claim

An assertion awaiting validation

Signal

A weak indicator requiring accumulation before action

Structure your organisation's knowledge for AI.