Xient Local LLM · AI Governance
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Powerful AI.
In your own house.
Your AI where your data is - on your hardware, under your control. We bring the right model securely into operation, optimised for your purpose, without a single record ever leaving the house.
Level up your AI.
Book an intro callWhy local
Some data doesn't belong in others' hands.
Cloud AI is convenient - but not for every case. Where business secrets, sensitive data or regulatory requirements are involved, your own house is the safest place. Local language models and generative AI are now powerful enough to make exactly that possible.
Data stays in-house
No content leaves your network - no foreign browser tab, no copy.
No external dependency
Independent of non-European cloud constraints and shifting pricing models.
Full control
Model, data and operation are yours - traceable and predictable.
The ambition
AI in-house. Sovereignty by design.
Local AI isn't a hobby project. It needs the right model, the right hardware and secure operation. That's exactly what we set up - and we support it so it holds up in daily work.
Your AI. Your house. Your control.
How it works
From model to secure operation.
Not the biggest model. The right one.
NVIDIA DGX Spark - a compact AI machine for the desk. One example from our practice, not a sales offer.
The hardware
From the desk to the data centre.
Powerful AI no longer necessarily needs the cloud. We don't sell hardware - we advise and give a recommendation: which setup fits your scenario, and how deeply it should integrate with your existing datasets, architectures and agents.
From a Raspberry Pi as a proxy to the NVIDIA H200, we know the whole range from our own experience. Talk to us - and we'll find the right setup and the right degree of integration together. SAP integration is always included on request.
Three devices for orientation - illustrative, not exhaustive. Hardware is optional with us: we advise, size it and support operations - procurement stays with you.
Raspberry Pi
- Role
- Routing & gateway - distributes requests, sits in front, orchestrates. Holds no large models itself.
- For whom
- First steps, edge and front-end nodes.
- Models (illustrative)
- No large language models - at most very small helper models. Its purpose is routing.
- Concurrency
- Intended as a gateway, not for inference of large models.
- Hardware
- Compact ARM single-board computer.
NVIDIA DGX Spark
- Role
- Prototyping, fine-tuning and local inference right at the workplace.
- For whom
- Individual developers or a small team.
- Models (illustrative)
- Fine-tune up to ~70B parameters, inference up to ~200B on one unit, up to ~405B with two units linked - open models such as Llama, Mistral, Qwen or DeepSeek.
- Concurrency
- Development and validation, single users - not high-volume production serving (memory bandwidth caps throughput).
- Hardware
- GB10 Grace Blackwell, 128 GB unified memory, up to ~1 PFLOP (FP4).
NVIDIA H200
- Role
- Production inference in the data centre, for many users at once.
- For whom
- Several developers and many concurrent users.
- Models (illustrative)
- Large language models in production - e.g. a 70B model fully on one card, models beyond 100B parameters, 405B models across several GPUs, plus long contexts and large batches.
- Concurrency
- Many parallel requests; splittable into isolated instances via MIG (multi-tenant). Illustratively ~30,000 tokens/s on a 70B model - theoretical, depending on model and stack.
- Hardware
- Hopper, 141 GB HBM3e, 4.8 TB/s, up to ~4 PFLOPS (FP8); eight cards (HGX) ≈ 32 PFLOPS.
Orientation, not a price list: illustrative figures per vendor specifications - actual values depend on model, quantisation, load and depth of integration. From the Raspberry Pi through the DGX Spark to the H200 class, we know these devices and work with them from our own experience - we recommend what fits your scenario rather than selling devices.
As much local as possible, as little cloud as necessary.
Our principle - so you stay as lean as possible in an AI-governance context.
Security
Optimal for the purpose. Risks under control.
Local doesn't automatically mean secure. We bring the discipline a productive AI operation needs - from the vetted model to gapless traceability.
Vetted model
Only what has a good Trust Score via Xient Trusted LLM runs - known provenance, assessed risks.
Hardened environment
Set up secured and isolated, by the principles we also apply in cybersecurity.
Identity & least privilege
Who may do what - clearly governed, instead of open access for everyone.
Audit & monitoring
Traceable in operation: who used what when, and whether everything runs as intended.
Which model is trustworthy is clarified by Xient Trusted LLM. How we secure operation is shown by Cybersecurity.
Why Xient
Advised, built, operated.
Local AI is a question of selection, architecture and operation - exactly our disciplines. We don't deliver one piece, but the whole path. AI isn't a hype topic for us, but a craft we run productively ourselves.
Selection
The right model for your purpose - vetted, not guessed.
Build & operation
Put into secure operation and looked after in daily work.
Optimisation
Fine-tuned for your tasks - performance where it counts.
A powerful AI in your own house - selected, securely operated and optimised for your purpose.
FAQs
What decision-makers ask first.
Does our data really stay in-house?
Yes. Model and data run on your hardware, in your network. There's no detour via a foreign cloud and no copy to the outside.
What hardware do we need?
That depends on the model and load - from a compact AI machine like NVIDIA DGX Spark for the desk to data-centre class. We size it to fit need and budget.
Which models run locally?
Open and open-source language models in various sizes. We make the right choice via the vetted database of Xient Trusted LLM.
How does this relate to Xient Trusted LLM?
Xient Trusted LLM tells you which model you can trust. Xient Local LLM puts exactly that model into secure operation - in-house, optimised for your purpose.
Is local worth it versus the cloud?
For sensitive data, predictable costs and full control, often yes. We work it through honestly with you instead of selling a direction.
Your AI belongs in your house.
We choose the right model, put it into secure operation and optimise it for your purpose - sovereign, traceable, with risks under control.