Local AI.
Sovereign by design.
A platform for your knowledge, your voices, your agents and your avatars — entirely on your infrastructure, in your country, under your control.
Not a roadmap. A turnkey AI platform — 20+ models for text, speech, vision, video, music and avatars, integrated and production-tested on local hardware. Deploy the full stack, or start with the one component that solves your most urgent constraint.
Built on this stack.
Packaged to deploy.
Each Aethos product works standalone or as part of the integrated platform. Click any product to see capabilities, use cases and technical specifications.
Aethos RAG
Enterprise knowledge retrieval with source-cited answers across all your data sources.
Explore Autonomous CodingAethos Coder
Plans, writes, verifies and delivers code changes across your codebase. On-premise. Auditable.
Explore Speech AIAethos Voice
Local speech recognition and synthesis with voice cloning. No audio leaves the building.
Explore Digital HumansAethos Avatar
MetaHuman-grade digital humans with real-time facial animation, emotion synthesis and lip-sync.
Explore Immersive ExperiencesAethos VR
Training simulations, virtual exhibitions, showrooms and live event stages on Unreal Engine 5.
Explore
The cloud knows your customers
better than you do.
Every productive AI interface bought today is also a data outflow. For an organisation with high sovereignty requirements, that is not a compliance detail — it is the foundation of the business.
Sovereignty is not negotiable.
GDPR, NIS-2 and sector-specific regulations require that business data and sensitive content remain under your control. Public-cloud AI APIs see everything they are shown — and reserve training rights on it.
Latency and cost scale the wrong way.
Per-token billing gets expensive the moment a use case grows. With every increase in adoption you pay providers — instead of building an asset. Availability hangs on a third party's contract.
Knowledge you train is not yours.
Models you fine-tune on hyperscaler APIs are fragile as assets. If licence, price or availability changes, years of work evaporate — classic lock-in.
Four fields with
immediately visible returns.
Internal knowledge portal for employees
RAG across Confluence, SharePoint, internal wikis, runbooks, specifications, ticket histories and engineering decisions. Answers in natural language, with source citations. Reduces tier-1 escalations and makes onboarding colleagues productive from week one.
Coding agent for engineering teams
Aethos Coder inside your network. Pull-request reviews, test generation, refactoring across enterprise repositories. Even sensitive areas such as financial transactions, compliance workflows or production control stay sovereign — no code snippet leaves the data centre.
Voice agent for service desks & hotlines
Local STT & TTS plus LLM for service-desk requests, orders, status queries or self-service scenarios. Multilingual (English, German, further languages), with seamless handoff to human agents. Full conversation telemetry stays in your hands — GDPR-compliant, without third-party APIs.
AR/VR training for safety-critical work
Maintenance procedures, safety protocols, onboarding and complex manual steps as immersive training with an AI coach. The avatar spots mistakes in the workflow, answers questions, documents progress. Scales training without training rooms — and without sensitive process documentation leaving the secure zone.
Your hardware.
Your data. Your tempo.
Aethos is optimised for modern local hardware — from NPU-driven edge nodes to GPU clusters in the data centre. The figures below come from production measurements on our reference platform.
Three deployment modes, one stack.
Air-Gap
Fully isolated deployment in protected zones. No outbound network traffic. Updates via signed packages. Suited for particularly sensitive areas.
On-Premise
Classic installation in your data centre. Central model and skill registry. Integration with SSO, LDAP, SIEM and existing audit pipelines.
Hybrid Edge
Local NPU nodes in branches, field notebooks or VR stations, synchronised with the central data centre. Low latency on-site, central data control.
Twice gold.
On stage.
Best Event Awards · International Jury
Let us start with what
proves itself immediately.
We recommend a staged entry: a one-day architecture workshop, a six-week proof of concept, then a pilot operation with real users. Each stage is valuable on its own and decides on the next.
Architecture workshop
1 day · on siteWe map your priority use cases, survey the existing data landscape and design the target architecture.
- Use-case mapping
- Data & compliance audit
- Feasibility assessment
- Roadmap draft
Proof of concept
6 weeks · sandboxOne priority use case, running in your test environment with real data, clear success metrics and clean handover.
- Local model deployment
- RAG across your data sources
- User-acceptance measurement
- Handover documentation
Pilot operation
3–6 months · productionProductive pilot with real users, full telemetry, tuning cycles and documented handover to your internal teams.
- SLA & monitoring
- Skill and model tuning
- Training of your teams
- Scaling plan
Local AI is not a product you buy.
It is an asset you build.
Tell us about your organisation and where sovereign AI could make the biggest difference. We will get back to you within two business days.
Ferrogasse 59, 1180 Wien
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Nestoros 1, 15231 Chalandri
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