Physical & Industrial AI / Sovereign AI

Sovereign AI. Control you can verify.

Choose and adapt AI around your work. Define where information goes, which actions are permitted and how your team can operate, improve and replace the system.

Independent product leadership. Worldwide, with an EU focus.

Request a quoteExplore the decisions
Authority flowInformation in. Authority retained.
Named operating owner01
Authorised request

Identity, context & decision controls

Approved contextIdentity · access · provenance
Qualified modelVersion · rights · evaluation
Proposed answer or action
Permission & approval gateEnforced outside the model
Within authorityPermit a scoped tool request
Outside authorityRefuse or escalate

Tool or external systemQualify its own data boundary; verify the effect and return evidence to the operating owner.

Inspect operational connections too.Logs · telemetry · backups · support · updates

Illustrative authority flow. Map every actual connection and location before deployment.

Start with the work.

A useful system begins with an owned business problem. Connect the commercial decision, research evidence and software or hardware constraints before choosing a model.

Choose a concrete starting point.

Three applications within the existing engagements. Start with the decision you face; each scope is quoted individually.

Product Decision Review

Model and Sovereignty Decision

A model choice, sensitive-data use case or supplier renewal needs a defensible decision.

What you leave withA small, evidenced shortlist and a clear proceed, revise or stop recommendation.

Scope, acceptance and responsibilities
Before work starts
A decision owner and deadline; the workload, data classes and procurement constraints; available proposals and test results; an intended operating owner.
How the work runs
  1. Frame the decision and the current or conventional baseline.
  2. Compare a small shortlist against the same rights, data, authority and operating requirements.
  3. Review the evidence, dissent and unresolved questions with the decision owner.
Agreed artifacts
  • Workload and acceptance brief, with mandatory constraints.
  • Exact-release and supplier comparison, deployment boundary and cost assumptions.
  • Decision dossier and, where needed, a separately scoped experiment or procurement brief.
Acceptance
Each hard requirement is addressed and material claims have dated sources. The sponsor can decide, or can see exactly which missing evidence prevents commitment. Choosing no model is a valid result.
Who owns what
Hyperion owns the agreed analysis. Your organisation owns the business decision, procurement and legal determinations; suppliers remain responsible for their contracted commitments.
Scope limits
A Review uses available evidence. New model experiments, integration, production approval and independent legal, security or safety assurance are outside this advisory scope.
What shapes the quotation
Number of credible options, evidence quality, jurisdictions and decision-makers. Scope, available capacity and fees are agreed by quotation.
The next decision
Buy directly, commission a bounded evaluation or implementation, revise the requirement, or stop.
Discuss this application View the engagement

Product Leadership Mission

Private Industrial Knowledge

Engineering or service teams lose time finding the correct approved manual, part revision or technical record.

What you leave withOne agreed knowledge workflow, with source evidence, permission checks and an explicit response when an answer is unsupported.

Scope, acceptance and responsibilities
Before work starts
A corpus owner and usable rights; revision and part identifiers; an authoritative permission source; domain reviewers, platform capacity and an operating owner; an approved execution environment.
How the work runs
  1. Record the current search baseline and freeze representative held-out questions.
  2. Qualify document extraction, retrieval and generation separately; build the agreed read-only integration.
  3. Evaluate failures as well as useful answers, then rehearse updates and recovery with the operator.
Agreed artifacts
  • Corpus, revision and permission manifest, plus baseline and candidate evaluation records.
  • The agreed code, configuration and interface for citations and abstention.
  • Failure register, operating instructions and an acceptance recommendation.
Acceptance
Agreed task and citation criteria, denied-access and outdated-document cases, representative load and human review effort are checked. The operator reproduces the agreed workflow. An accepted evaluation can conclude that rollout should not proceed.
Who owns what
Hyperion leads the named product and integration milestone. Your organisation supplies domain, platform and acceptance owners. Independent specialists review Hyperion-authored components where required.
Scope limits
No plant actuation, unlimited document cleansing, enterprise-wide rollout or ongoing managed service. Model and infrastructure work requires the rights, people and environment named in scope.
What shapes the quotation
Document formats, languages, revision quality, permissions and integrations determine effort. Founder, client and specialist capacity are named separately in the quotation.
The next decision
Harden and roll out the accepted boundary, buy a suitable platform, address a measured gap, or close the pilot.
Discuss this application View the engagement

Product Leadership Mission

Supplier Acceptance and Exit

A supplied AI system is approaching acceptance, renewal, migration or replacement.

What you leave withEvidence of what your team can operate, recover and replace, with unresolved dependencies made explicit.

Scope, acceptance and responsibilities
Before work starts
Permitted access to an agreed test environment; requirements, contracts, artifacts, logs and versions; a supplier contact and client operators; authority for the agreed non-destructive exercises and usable replacement rights.
How the work runs
  1. Map requirements and supplier commitments to reproducible checks.
  2. Exercise key workflows, restoration and one agreed replacement scenario within the approved test boundary.
  3. Have a client operator rerun the handover and review residual gaps with the acceptance owner.
Agreed artifacts
  • Requirement-to-evidence matrix, artifact inventory and execution records.
  • Observed portability differences and recovery, handover and exit instructions.
  • Acceptance conditions, remedial responsibilities and remaining dependencies.
Acceptance
An operator who did not author the runbook completes the agreed exercises. Both failures and successes are recorded. Replacement is judged on accepted task behaviour and operating cost, not API compatibility alone.
Who owns what
Your organisation decides acceptance. The supplier remedies its system. Hyperion evaluates the agreed boundary; review of Hyperion's own implementation is not independent assurance.
Scope limits
No emergency migration, legal opinion, destructive production testing or incident-response SLA. A document-only pre-purchase decision belongs in a Product Decision Review.
What shapes the quotation
System boundaries, access, supplier cooperation, dependency count and the chosen replacement scenario determine the quotation.
The next decision
Accept with stated conditions, require supplier remediation, commission a scoped migration, or retain the current arrangement.
Discuss this application View the engagement

Private industrial knowledge

Help engineering and operations teams find approved information in manuals, service records and technical documents, with access controls, citations and a clear response when evidence is missing.

What evidence would make an answer useful enough to act on?

Explore industrial knowledge systems

Governed workflows and augmented teams

Give a founder or team useful assistance with preparation, analysis and bounded tool actions. Assign a human owner to accepted work, business commitments and exceptions.

Which work can be delegated, and which decisions stay human?

Explore agents and augmented teams

Local and field assistance

Evaluate a device or site deployment when connectivity, latency or information constraints justify it. Test the actual hardware, operating conditions and update path.

What must still work when the connection, model or device fails?

Explore embedded and edge systems

These are illustrative engagement situations, not claims of completed client deployments. Forecasting, optimisation, perception and machine control require their own methods and acceptance evidence.

Make the boundary explicit.

Sovereignty is a set of practical controls over data, technology and operations. An open-weight model or a European endpoint answers only part of that question.

Information

Map prompts, documents, retrieved context, outputs, embeddings, logs, backups, telemetry and support access. Identify every recipient and retention requirement, including services outside the inference runtime.

Authority

Bind identities to approved data and tools. Treat model output as a proposal: enforce permissions outside the model, require approval for agreed consequential actions and verify the effect before reporting success.

Change and exit

Record versions, configuration, licences, operator access and dependencies. Plan evaluation after changes, export, replacement and rollback. Portability must be demonstrated for the workload, not assumed from a file download.

Choose how it runs.

Choose an operating arrangement against the workload and your team's capacity. These are alternatives to qualify, not a ranking of sovereignty.

Device or site

A suitable local model may reduce dependence on remote inference. Your operating plan must still cover hardware, identity, patching, updates, logging, backups and any outbound connections.

Can the named team maintain the system and recover it in the field?

Private cloud

A controlled tenant or dedicated environment can connect AI to existing identity and operations. Establish who administers each layer, where records reside and which supplier services remain involved.

Which infrastructure and support access remain outside your organisation?

Approved hosted services

Managed inference can reduce infrastructure work. Qualify the exact endpoint, retention, geography, feature support, lifecycle and contractual terms for the information and actions involved.

Does the whole service meet the boundary, including its control plane?

Qualify models and actions.

Evaluate Mistral, Qwen, GLM, Kimi, DeepSeek, appropriate Google Gemma releases and suitable alternatives against the same acceptance criteria. Model origin, model rights, inference provider and deployment location are separate decisions.

Select an exact release

Record the task, languages, baseline, checkpoint or API version, rights, runtime and resource requirements. Evaluate useful outputs and important failures. A smaller model or conventional system may be the better choice.

Model selection and evaluation

Adapt where evidence justifies it

Compare configuration, prompting, retrieval and tool design before adding training. When tuning is justified, define data provenance, held-out evaluation, regression checks and ownership of the resulting artifacts.

Configuration, inference tuning and adaptation

Secure the AI system

Threat-model data access, prompt injection, tool authority, supply-chain dependencies and recovery. Guard models can contribute a layer; they do not replace access control or independent assurance.

Cybersecurity for AI

Use AI in security work

Scope analyst assistance, triage or evidence preparation with controlled inputs and human review. Keep incident authority and security decisions with the responsible people.

AI for cybersecurity

Open weights are not automatically open-source AI. Check the exact model and derivative licences separately from hosting and service contracts. The model recommendation remains independent of provider origin or branding.

Separate the model from the service.

A shortlist can combine suppliers. Qualify each layer against the same workload and operating boundary.

Model releases
Mistral · Qwen · GLM · Kimi · DeepSeek · Google Gemma

Choose the exact checkpoint or API version, permitted uses and task evidence. Generation, embeddings, vision and tool routing are different jobs.

Distribution and runtime
Hugging Face Hub · llama.cpp · Ollama · vLLM

A model repository, local serving tool and production runtime have different responsibilities. Check artifact provenance, compatibility, configuration, updates and operator capacity.

Infrastructure and supplier services
Your hardware or private platform · approved hosted services

Qualify NVIDIA components, Mistral services, Hugging Face hosting, Google Cloud or other suitable suppliers at the layer actually used. Contracts, support access and control-plane data remain separate from model rights.

Independent selection, worldwide with an EU focus. No vendor partnership or preferred-provider commitment is implied.

Exact releases, different qualification questions.

These dated release examples illustrate diligence across providers. They are not the latest-model shortlist, a ranking, a partnership claim or evidence of Hyperion running these models.

Model-card declarations and linked licence files are identified separately. Before use, verify the selected artifact revision, weight and code rights, adaptation and distribution conditions, and any hosted-service terms. A provider’s origin or an open-weight licence does not establish sovereign operation: hosting, administrative access, telemetry, retention and contracts still matter.

Explore Mistral for industrial systemsApplications, platform choices and deployment boundaries.

Make ownership deliverable.

Connect business, research and engineering through records that another team can inspect and maintain. Agree the actual artifacts and acceptance conditions in the quotation.

Decision record

Workload and baseline, candidate options, rights and operating constraints, available evidence, unresolved questions and a proceed, revise or stop recommendation.

Evaluation and implementation pack

The agreed code or configuration, test inputs, evaluation procedure, observed failures, authority rules and acceptance results. Distinguish illustrative examples from measured work.

Operating handover

Named owners, dependencies, maintenance and change process, failure escalation, recovery, export and replacement instructions. Your organisation or designated operator retains ongoing operation; Hyperion does not provide an ongoing managed service.

For founders and growing teams, begin with one workflow and a realistic maintenance owner. TransformationOS and LaunchpadOS provide related venture context; their published maturity records define what currently exists.

Hyperion
The product decisions, implementation, evaluation and handover named in the engagement.
Your organisation
Data rights, system ownership, approvals, an operating owner and the required engineering and safety resources.
Technology suppliers
Their contracted models, platforms, infrastructure, integrations, support and release obligations.

Deliverable IP rights follow the engagement terms; model rights follow the applicable licence or vendor contract. Product leadership does not replace independent legal, safety or cybersecurity assurance.

TransformationOS LaunchpadOS Sovereign Fabric research

Start with the right mandate.

For startups through large enterprises, worldwide with an EU focus. Choose the decision and delivery responsibility you need; scope and fees are provided by quotation.

  1. Which approach should we choose?

    Product Decision Review

    Frame the requirements, review available evidence, compare options and establish the next decision. Where evidence is missing, define the evaluation needed. Implementation is excluded.

  2. Can we establish one accepted capability?

    Product Leadership Mission

    Lead one agreed milestone, with the code, configuration, integration, evaluation and handover explicitly included in scope. Name client and specialist capacity before delivery commitments are made.

  3. Who holds the product decisions across teams?

    Executive Product Leadership

    Establish an agreed leadership mandate, priorities, decision rights and acceptance cadence across products and suppliers. Engineering, operations and independent assurance capacity remain explicitly allocated.

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Practical questions.

Does sovereign AI require self-hosting?

The required controls determine the arrangement. Self-hosting can offer control over particular layers, but also creates operating responsibilities. Hosted services can fit some requirements when their technical and contractual boundaries are acceptable.

Do we need to fine-tune a model?

Not necessarily. Establish a baseline and compare configuration, retrieval and workflow changes first. Fine-tuning is justified when it addresses an evidenced gap and its data, evaluation and maintenance requirements are viable.

Can we use models from different providers?

Yes, a scoped evaluation can compare ecosystems or assign different tasks to different models. Each release and service needs its own rights, data-flow and operational checks; interchangeable APIs alone do not prove interchangeable behaviour.