Product · Helios Brain

The Living
World Model Factory.

Compile your ontology, data, and action space into a private model of how your organisation actually works. Simulate change, govern action, measure reality, learn over time.

Research & insights
What it is

A model is not a neural net.
It is a substrate.

A world model is
W=( O, G, N, D, S, A, C, R, P, E, V )
OGNDSACRPEVHELIOSBrain runtimeW = (…)
O
Ontology
Domain types, units, rules
G
Graph state
Bitemporal entities & edges
N
Observations
Sensors, events, ingest
D
Memory
What was seen and when
S
Simulation
Forward state evolution
A
Actions
Available interventions
C
Causality
Effect estimates, refuted
R
Reasoning
Eight cooperating solvers
P
Provenance
Every number to its source
E
Evaluation
Predictions vs outcomes
V
Validation
Governance & constraints
Inside the substrate

Thirteen things, working together.

§ 01
Data sources

ERP, CRM, documents, telemetry, connected, not copied.

§ 02
Ontology

The shared language of your organization.

§ 03
Knowledge graph

Entities, relationships, history, kept current.

§ 04
Memory

What was known, when, and by whom.

§ 05
Agents

Specialists that act on the model, under governance.

§ 06
Tools

The actions and APIs your organization can call.

§ 07
Permissions

Who can see what, do what, decide what.

§ 08
Rules

Policy, compliance, constraints, enforced at runtime.

§ 09
Simulations

Forward state, what if we did this?

§ 10
Predictions

Time-stamped expectations the model commits to.

§ 11
Outcomes

What actually happened, ledgered to the prediction.

§ 12
Human feedback

Tacit knowledge captured weekly from experts.

§ 13
Governance

Provenance, audit, adversarial checks, native.

How it operates

A model that improves itself.

01
Build
Compile ontology, evidence, eight reasoning layers.
02
Optimize
Search the action space against constraints.
03
Predict
Turn every recommendation into a committed outcome.
04
Act
Execute through governed tools, agents, decisions.
05
Measure
Record what actually happened. Outcomes ledgered.
06
Evaluate
Score prediction against reality. Where it drifted.
07
Learn
Capture corrections, attribute to evidence.
08
Feedback
Push learning back into the model so the loop sharpens.
Build → Optimize → Predict → Act → Measure → Evaluate → Learn → Feedback → Rebuild
Use it everywhere

Once built, the model is callable from anywhere.

API

Your applications

Embed the world model in CRM, ERP, or any internal tool.

MCP

AI agents

Governed organizational reality for your existing agents.

SDK · CLI

Pipelines

Run the model from code. Validate, score, decide, log.

Decks

Decision rooms

Run scenarios with your team, inside Helios.

Helios Brain, in numbers
13
Substrate components, data to governance
9
Steps in the core learning loop
100%
Decisions traceable to source
Not the old shapes

Adjacent categories each capture one piece.

None is the substrate that holds them together.

Helios Brain
World Model Factory
State
Actions
Causality
Simulation
Outcome learning
Governance & provenance
RAG
Retrieval grounding
State
·
Actions
·
Causality
·
Simulation
·
Outcome learning
·
Governance & provenance
~
Agent builders
Tool orchestration
State
~
Actions
Causality
·
Simulation
·
Outcome learning
~
Governance & provenance
·
Digital twins
System representation
State
Actions
~
Causality
~
Simulation
Outcome learning
~
Governance & provenance
~
Workflow automation
Repeatable execution
State
~
Actions
Causality
·
Simulation
·
Outcome learning
~
Governance & provenance
~
BI / analytics
Dashboards
State
Actions
·
Causality
·
Simulation
·
Outcome learning
·
Governance & provenance
~
full partial missing

Build your organization’s world model. Use it everywhere.

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