AI
Use AI without handing organizational effect over to AI
AI Control Machine
Binds the complete effect-relevant AI stack of an instance, including inputs, models, providers, roles, decisions, evidence and consequences.
Which effect problem, sovereignty model, and formation path fit your situation?
Every public machine description must answer: operator, sovereign effect space, Target rule source, and concrete formation path.
Sovereignty labels:
- O — operator-sovereign
- U — user-sovereign
- M — mixed root sovereignty
- O/U — instance-selectable
Delegated sovereignty is an additional bounded axis.
There are two formation paths: self-build and prepared SSMFF formation/installation.
SSMFF may be marked as a Formation Machine in discovery because its machine purpose is formation of a separate Target. This is not ranking or recommendation.
For a prepared solution:
operator/publisher provides Target rule templates -> sovereign selects/authorizes -> SSMFF binds
Public catalogue invariant:
- 23 generic public C0 identities
- 14 company/product-specific C0s INTERNAL ONLY
- 1 identity conflict blocked
Machine cards may expose compact Sovereignty and Formation fields. Detail pages must explain the full topology and claim boundary.
5 · PUBLIC ARCHITECTURE CATALOGUE
Describe your effect problem – not the software you want to buy.
Search works deterministically over the published catalogue text and tags. Matches remain in stable order. There is no personalized recommendation, semantic similarity ranking, popularity boost, or paid placement.
These entries are presentation aids for readers. They are not a normative SES taxonomy.
23 architectures in the current filterstable order · no ranking
No architecture matches these deterministic filters. This is not a negative judgment about your effect problem.
General reference architectures
These architectures are not bound to one named organization or product context.
Banking
Order bank-wide effect as a sovereign institution
Sovereign Effect Bank Machine
Architecture for a bank-wide effect order spanning risk, capital, liquidity, pricing, customer relation and other effect-relevant banking paths.
Provider effect
Use cloud without granting the provider unnecessary effect power
Provider-Blind Cloud Effect Control Machine
Binds provider-related effect, dependencies, cost and infrastructure paths so the provider may remain a technical carrier without becoming a normative source.
Vehicle
Place digital vehicle effect under a closed authority order
OEM Vehicle Effect Machine
Binds effect-relevant vehicle, OEM, provider and user paths into a controlled machine order.
Law firm
Place digital law-firm effect under professional authority
Law Firm Effect Machine
Binds professional, organizational, evidential and technical law-firm effect into a sovereign effect-relevant order.
Personal research
Structure your own research without foreign normative decision power
Personal Sovereign Research Effect Machine
Binds personal research effect, evidence and decisions into its own sovereign effect space.
Administration
Form an administrative procedure as controlled effect
SPARK Administrative Procedure Machine
Turns a complete administrative effect space into bound authority, rules, states, evidence and consequences.
Form a new SES machine
Form a new SES machine from an intended effect space
Sovereign SES Formation Factory Machine
Makes machine formation itself a controlled SES process. The domain and normative order is closed before a technical carrier is implemented from it.
Fashion
Control fashion effect as a closed effect space
Fashion Machine
Applies SES to effect-relevant flows of a fashion domain and binds their domain, organizational and technical effect.
Research
Make research controllable
Research Application Machine
Binds research question, test design, candidate and control, evaluation, classification, audit and publication decision into a closed research-effect order.
Legal effect
Bind internal digital legal effect ex ante
Sovereign Legal Effect Machine
Controls under which bound conditions a digital effect may be treated as valid internal legal effect within the instance.
Craft business
Recover scarce human work capacity
Craft Business Capacity Recovery Machine
Targets effect-relevant administrative load so that ruleable effect does not unnecessarily consume scarce professional capacity.
Bind dynamic infrastructure
Bring Kubernetes-carried effects into a closed scope
Kubernetes Baseline Binding Machine
Applies baseline binding logic to dynamic effect-relevant paths carried through Kubernetes environments.
Logistics
Control logistics effect across the complete effect-relevant flow
Logistics Effect Control Machine
Binds existing baseline effect and logistics domain effect into one composed SES machine.
Normative decision
Does an AI really need to decide?
Cognitive Intelligence Core Machine
Separates proposal, analysis and technical capability from valid normative judgment. AI may contribute without becoming the sovereign source of decision.
Payment
Make payment effect controllable ex ante
Bank Payment Acceptance and Execution Machine
Binds payment-related effect, authority, states, evidence and consequences inside a closed SES effect space.
Personal digital effect
Put personal digital effect back under your own rules
Personal Digital Control Machine
Orders effect-relevant digital paths of a personal instance so external technology does not gain normative power merely through technical capability.
Bureaucracy
Stop making people repeatedly administer fully ruleable effect
Bureaucratic Load Control Machine
Targets repeated human checking, approval and reconstruction work where the relevant effect can be fully closed through rules and evidence.
Safety
Allow safety-relevant effect only under bound authority
Safety Control Machine
Orders safety-relevant effect, authority, states, rules and consequences ex ante instead of relying only on post-hoc safety control.
Make machines discoverable
Publish, find and verify SES machines without platform power
Ownerless Machine Registry Machine
Binds registration, deterministic search, versions, download and integrity evidence without turning recommendation, ranking or marketplace logic into authority.
Authority
Separate technical capability from valid authority
Sovereign Identity and Authority Effect Machine
Binds organizational authority, delegation and effect-relevant roles so that access or technical power does not automatically create decision rights.
Meaning
Who determines what something means inside the machine?
Ontology Machine
Binds ontological meaning as an effect-relevant order and prevents technical fields, providers or models from silently creating normative meaning.
Recommended baseline for existing effect spaces
First understand and bind how effect actually arises in your environment today
Sovereign Effect Baseline Gate Machine
Binds the existing technical, human, organizational, and process effect reality under `allow-as-before` without already imposing new domain effect during baseline operation.
SEBG — bind existing effect, accelerate change
SEBG starts with allow-as-before: existing operational effect continues in baseline operation while effect-relevant interactions in the claimed scope become bound to scope, authority, rule, decision, state, evidence and revalidation.
A SEBG baseline does not replace the existing system landscape; it binds its actual effects. In suitable instances, this can allow a small qualified team to form the baseline with comparatively limited intervention and in a short time. Effort and duration remain instance-dependent; there is no universal team size or baseline duration.
The Decision-State-Evidence chain then forms a reusable instance basis for replay, simulation, rule design, policy dry runs, effect analysis and migration planning. New or changed rules can be tested in the Rule Laboratory against the bound effect reality before the sovereign activates them. Rule change therefore does not begin each time by reconstructing the existing effect reality and does not automatically have to become a classical software-change project.
The SES–SEBG–SEEM Authoritative Baseline v2.2.0 is a further architecture for applicable use cases, not a universal mandatory component of every SES machine.
Large effect does not automatically require a large SES compute load
SES controls effect through bound rules, states, decisions, evidence, consequences and revalidation. The scale of controlled effect and the compute-load class of the SES control path are not the same thing. High professional, organisational or economic effect scale therefore does not impose a correspondingly large universal hardware class on SES.
Technical carrier workload remains separate: a carrier may use AI, GPU, cloud or other compute-intensive components without making that workload intrinsic SES rule/state/evidence/revalidation work.
The C0 “Personal Smartphone Effect Boundary Machine (PSEB)” shows that smartphone-mediated effect can be architecturally defined as a personal SES effect space. This supports smartphone class as a possibility, not a claim that every SES machine can be productively operated on every smartphone.