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Core Engine · The Mind of Enterprise

The mind of
your enterprise.

Brain Engine joins your memory, processes, data, models and infrastructure into one loop that understands, acts and improves, inside the permissions and budgets you set.

Talk to us See the loop

In development. Described here as the target product.

The loop
Two levels
Build
Modules
MetaModel
Governed
The core idea

A digital organism that keeps working

Brain Engine does not wait for a prompt. It follows your business as it changes and carries every task through the same nine steps. Click a step.

Brain
Engine

Two levels of intelligence

One answers the task. One improves how tasks are solved.

Operational Brain runs the business day to day. The MetaModel works on a slower clock, on the structure that solves those tasks.

Operational intelligence

“What should be done in this situation?”

Understands the state, uses memory, predicts, selects actions, executes them and judges the result.

  • Runs on models, statistics, rules, procedures and solvers
  • Language models only where a result can be checked
  • Daily operations never depend on a constant LLM call

Architectural intelligence: MetaModel

“How should the system be built to solve this kind of task better?”

Chooses and combines computing components, evaluates the options and prepares verified architecture changes.

  • Compares candidates against your current setup
  • Keeps the current architecture if nothing is clearly better
  • Never puts its own output into production alone
Build your environment

From your documents to a working application

You describe the organisation. Brain Engine builds an application around how your business actually works: users, processes, data model and the order of operations.

1
Choose your sectorCombine several areas of activity if you need to.
2
Describe the organisationUnits, sites, people, customers, volume and business model.
3
Add connectionsYour cloud, servers, databases, APIs and supported MCP services.
4
Upload documents, clarify in dialogueBrain Engine joins them with sector knowledge.
5
Review the future applicationRoles, processes, data, planned actions and contradictions.
6
Pick the designCalendars, queues, maps, documents and analysis panels.
7
Set brand and governanceName, access, approvals, allowed autonomy and budget.
8
Review the resource planWhat gets built, which integrations, expected cost.
9
Receive your domainResources are prepared, checked, and your application opens.

What you get

Concrete, not abstract.

Your own applicationAn address and a space reserved for your organisation.
WorkspacesFor staff, managers and, when needed, customers or partners.
One consistent modelData, documents, processes and access rights fit together.
ConnectionsTo the external systems and sources you allow.
Applied AI functionsMatched to each role's tasks.
Infrastructure controlService status, compute resources and budget.
HistoryChanges, results, decisions and approvals.
Change by conversationSay “add a second branch” and review the change before it applies.
Modules

Many working parts, one system

A module is a functional subsystem, not necessarily a separate server. Each has its own responsibility, settings, output and links to the others.

Understand and build

Domain Brain & StudioTurns requirements into your application and its Domain Package.
Knowledge & semantic layerConcepts, relations and requirements, each linked to its source.
Data PlatformIngests, checks and prepares data with lineage.
Integration StudioConnects databases, APIs, files, clouds and MCP services.

Remember and predict

MemorySourced, versioned, time-aware context and experience.
ML Runtime / Model FabricTrains, versions, runs and monitors specialised models.
LLM & Cognitive RoutingPicks the right tool: memory, model, solver or an approved LLM.
Enterprise StateThe observed state of the business and its compact representations.
World ModelForecasts, scenarios and uncertainty.

Decide and act

Decision & OptimizationChooses among permitted actions and explains why.
Verification, Policy & AutonomyRights, approvals and autonomy limits.
Actions & OperationsTurns permitted decisions into work.
DurabilityExecution that resumes safely after failures.

Run and govern

StorageSnapshots, backups, clones and recovery points.
Control PlaneDesired vs. real state of the whole environment.
Infrastructure & ComputePrepares CPU, GPU, network and database resources.
FabricShared context, events and audit trail between modules.
Outcome Learning & HomeostasisChecks results and keeps the system healthy.
MetaModelDesigns and verifies the solving architecture.
Brain MetaModel

The engineer that designs how a task is solved

Different organisations have different goals. A clinic wants shorter waits, a warehouse wants better placement, a school wants better timetables. MetaModel searches for the combination of components that fits.

Take clinic scheduling. It can compare rules and optimisation, prediction and optimisation, or prediction with context and scenarios, then prefer the simpler one if quality and cost say so.

  • Components come only from an approved catalog
  • Candidates are tested on held-out scenarios against your current setup
  • A candidate runs in shadow mode first, with no outside actions
  • Approval, monitoring and rollback stay with people and existing controls
metamodel / experiment / clinic-scheduling
Candidate comparison
Illustrative example, not a measured result.
CandidateQualityLow costVerdict
ARules + optimisation
Baseline
BPrediction + optimisation
Recommended
CPrediction + context + scenarios
Too costly
Constraints respectedShadow evaluationRollback plan ready
Governed by design

Autonomy with limits you can inspect

A system that acts needs rules about when it may act. These are part of the design, not an add-on.

Permissions firstEvery read, transformation and action is checked against rights and policy.
People in the loopApproval chains, limits and expiry for anything that matters.
Full audit trailFrom source to computation, decision, action and result.
Tested before useNew models and architectures are evaluated and shadow-run first.
RecoverableBackups, durable execution and rollback to a previous version.
Honest limitsWhen evidence is missing the system hands over or keeps the current state.
FAQ

Frequently asked questions

What is Brain Engine?

The integrated digital mind of a business. It joins memory, processes, data, models and infrastructure into one loop of understanding, acting and improving.

Is it a chatbot?

No. It follows your operations, predicts, proposes and runs permitted actions. Language models are used only where a result can be checked, and daily operations do not depend on them.

Can it act without asking?

Only inside the actions, limits and autonomy levels you configure. Anything outside needs a person's approval, and every step is recorded.

How does it improve over time?

It compares results with expectations. Repeated misses lead to reviewing models or architecture through the MetaModel, with evaluation, shadow runs and approval before any change goes live.

Can it run in my own cloud or on my servers?

Infrastructure is a module of its own. Supported services can be placed in an approved cloud or on your servers, within the budget and permissions you set.

Is it available today?

Brain Engine is in development. This page describes the target product. Talk to us to follow progress or discuss your use case.

Give your business
a mind of its own.

Tell us about your organisation and we will show how Brain Engine would fit.

Talk to us Read the docs