Protect sensitive prompts
Keep internal questions, customer context, documents, and audio away from unmanaged public AI accounts.
Vianordis--:--:-- UTCVianordis / ED. 02 / 2026
§ 05.26 — Product
Inference
Use AI on private European GPU capacity instead of sending business data to public model clouds.
Inference gives your business a private place to run AI models for assistants, document work, customer service, voice, and automation. The goal is simple: get the benefits of modern AI while keeping prompts, documents, and audio under a European cloud and governance model.
01 — Problem
AI can help the business, but public AI APIs create uncomfortable questions.
Many companies want AI for summaries, customer service, document search, and internal assistants. The first practical question is where the data goes. If prompts, documents, recordings, or customer details are sent to public model providers, the business may lose control before the AI project even starts.
- Employees may paste sensitive business data into consumer AI tools because it is convenient.
- Public AI accounts can make it hard to explain data location, retention, and provider access.
- Self-hosting GPUs sounds safer but creates hardware, maintenance, and operational complexity.
- Voice and document AI often require several services, increasing data-flow uncertainty.
- Regulated teams need an AI path that supports oversight, documentation, and risk classification.
02 — Solution
Inference gives your AI projects a controlled European runtime.
Inference provides dedicated GPU-backed model serving as a managed service. Your applications, agents, or workflows can use a private AI endpoint while Vianordis handles the operational layer behind it.
- Run useful open models for chat, document assistance, classification, and automation.
- Keep AI execution inside a European cloud model instead of defaulting to public non-EU providers.
- Start with smaller workloads and scale toward larger models or higher throughput when the business case is proven.
- Use the same strategic AI foundation across Workplace, Skills, document intelligence, assistants, and custom applications.
03 — Benefits
Advantages for business visitors.
Inference is not just GPU rental. It is the AI engine room for organizations that want practical AI without losing control of data flows.
Enable real AI products
Power assistants, RAG search, summarization, document intelligence, ticket triage, and voice agents.
Avoid GPU operations
Use managed capacity instead of buying cards, installing drivers, tuning runtimes, and monitoring hardware.
Start at the right size
Begin with a smaller tier for practical workloads and scope larger capacity only when the use case demands it.
Support AI governance
A controlled runtime makes it easier to document where AI processing happens and how it is accessed.
Build a long-term AI base
The same private inference approach can support multiple products and workflows over time.
04 — How it works
How a business starts with private AI.
- 01
Pick a valuable AI use case
Choose one practical workflow: customer support summaries, internal document search, meeting preparation, ticket classification, or a voice assistant.
- 02
Connect it to private inference
Your app or agent points to a managed European AI endpoint rather than a public model account.
- 03
Review risk and scale
Measure quality, latency, cost, and regulatory fit before expanding to more teams, models, or workflows.
05 — Features
What visitors should remember.
Private AI runtime
Run AI workloads on dedicated European GPU-backed capacity.
Works with existing apps
Applications can connect through familiar AI API patterns.
Chat and voice
Support both text-based assistants and speech-oriented workflows.
Managed operations
Vianordis handles the infrastructure side so the business can focus on use cases.
Scalable tiers
Start small, then scope medium or cluster capacity when model size or demand increases.
Technical notes available
IT teams can review model serving, runtime, access, and status details in the support section.
06 — Architecture
What this means operationally.
For a business buyer, the important point is not the GPU model. It is that AI processing can be made part of a controlled cloud architecture instead of an uncontrolled external dependency.
- Business applications or agents send AI requests to a private endpoint.
- The endpoint runs on European GPU capacity managed by Vianordis.
- Access can be controlled through the same platform posture used by other Vianordis services.
- Larger or more demanding workloads can be scoped as the business case grows.
- Technical implementation and current capacity notes are kept in the support app section.
07 — Use cases
Where Inference creates visible value.
Internal assistant
Give employees a private AI helper for company knowledge and daily work.
Document intelligence
Summarize, classify, translate, and search documents without using unmanaged public model APIs.
Customer service
Prepare answers, classify requests, and summarize customer history inside a governed environment.
Voice workflows
Build private speech-to-text and text-to-speech workflows for support, accessibility, or operations.
Regulated AI pilots
Test AI use cases where data location, oversight, and documentation matter from day one.
Product AI backend
Power AI features inside Workplace, Skills, Spectra, or custom business applications.
08 — Integrations
What it connects from a business perspective.
Inference is the private AI runtime that other Vianordis and customer applications can use.
Workplace
Shows how this service fits into the wider Vianordis environment instead of standing alone.
Skills
Shows how this service fits into the wider Vianordis environment instead of standing alone.
Document intelligence
Shows how this service fits into the wider Vianordis environment instead of standing alone.
Customer service
Shows how this service fits into the wider Vianordis environment instead of standing alone.
Internal assistants
Shows how this service fits into the wider Vianordis environment instead of standing alone.
Voice agents
Shows how this service fits into the wider Vianordis environment instead of standing alone.
RAG search
Shows how this service fits into the wider Vianordis environment instead of standing alone.
Business apps
Shows how this service fits into the wider Vianordis environment instead of standing alone.
AI governance
Shows how this service fits into the wider Vianordis environment instead of standing alone.
European infrastructure
Shows how this service fits into the wider Vianordis environment instead of standing alone.
Technical support
Shows how this service fits into the wider Vianordis environment instead of standing alone.
Custom workflows
Makes actions reviewable before work is executed or escalated.
09 — Trust
Regulatory implications in plain language.
Inference helps answer a basic regulatory question: where does AI processing happen? It does not remove all AI Act or GDPR duties, but it gives organizations a more controlled foundation for AI use.
AI Act direction
Vianordis is building toward full EU AI Act alignment across its cloud stack, including documentation, human oversight, traceability, and risk-aware AI operation.
Data location
The product is designed for AI processing on European infrastructure rather than unmanaged public model clouds.
Risk classification
Customers still need to classify their own AI use cases under the EU AI Act and decide which controls apply.
GDPR posture
Private inference can reduce unnecessary transfers, but customers must still define lawful basis, retention, and data minimization.
Human oversight
Inference provides model execution; business decisions should still include appropriate human review.
Technical evidence
Capacity, runtime, integration, and status details are available in the support app notes for technical review.
10 — Pricing
Start with one AI workflow, not a vague AI strategy.
Inference starts from published private GPU tiers, but the right size depends on model, data, latency, volume, and governance requirements. A demo should focus on one measurable business workflow.
11 — FAQ
Questions buyers usually ask.
Why not use a public AI provider?
Public providers can be useful, but they often create questions about data transfer, retention, provider access, and regulatory accountability. Inference is for organizations that want a more controlled path.
Do we need to understand GPUs?
No. The business decision is about whether private AI capacity helps a workflow. Technical sizing can be handled during scoping.
Is this only for large companies?
No. Smaller organizations can start with focused use cases such as internal search, support summaries, or private assistants.
Does private inference make us AI Act compliant?
No single infrastructure product can guarantee that. It supports a stronger compliance posture, but customers still need to govern the use case, users, data, and decisions.
What should we try first?
Choose a task where sensitive data and time savings both matter: document search, customer support, inbox summaries, or internal assistant workflows.
12 — Next step
Build AI on infrastructure your business can explain.
An Inference demo can show how a private European AI endpoint supports a real workflow without starting from public-model dependency or GPU operations.