Make your world legible to neural systems.
Turn semantic structure into neural representations.
IQ maintains a living semantic world model: entities, relationships, state, events, history, evidence, uncertainty, and meaning.
Neural models cannot consume that world directly. The Neural Projector is the bridge.
Not a vector database. Not a memory dump.
Semantic world
IQ keeps the real structure of your world: entities, relationships, provenance, state, and change over time.
Neural Projection
It derives neural representations from that world while retaining the context that gives them meaning.
Neural systems
LLMs, embeddings, and other models consume that signal without losing sight of your world that created it.
Semantic structure becomes neural signal.
World model
your world remains explicit and queryable. Facts are not just floating tokens; they are grounded in identity, state, and history.
Projected representations
Neural projections are derived from that world, and updates ripple out without losing the semantic structure beneath them.
What it produces
Embeddings
Dense neural views of entities, relationships, and concepts.
Context
Live, structured context for reasoning instead of stale prompt fragments.
Training data
Grounded examples derived from your world with provenance and meaning.
Signals
Change signals that can flow into systems without losing identity.
Groundedness matters.
Identity
The same entity stays the same across symbolic, semantic, and neural views.
State
A fact is understood in terms of what is known, what changed, and what remains uncertain.
Provenance
Every representation still carries the source and logic that produced it.
World-first. Model-agnostic.
IQ is not trying to force one model to become your world. It gives every model a coherent world to operate on.