AI & Compute – Query your corporate knowledge · knowledge management with AI – fast, secure, scalable

Knowledge management: your corporate knowledge, queryable

Make documents, wikis and repositories searchable with AI – as a RAG system on your own infrastructure so that corporate knowledge stays in-house. Use knowledge instead of searching for it: information is often scattered across different systems, hard to find or outdated – a RAG-capable AI assistant on reliable, GDPR-compliant, C5-attested infrastructure solves this.

ccloud³ Console · RAG assistant
eu-de · Hallstadt Data Centre
Documents
48,000 indexed
Answer
1.8 s
Data leakage
0
ING Ingest pipeline · Kubernetes
● Up to date
VEC Qdrant · NVMe volume
● Running
LLM vLLM · RTX A4000
● Serving
S3 Sources · object storage
● Stored
Answer with sourcemanual v7 · page 12
  • Powerful language model with context processing – analyses complex internal documents precisely, generates context-based results and links company-specific knowledge.
  • Ease of use as a success factor – queries in natural language, quick access to the information needed without technical knowledge.
  • Data sovereignty through self-hosting – complete control over sensitive company data, maximum data protection compliance, independence from external providers.
  • Professional infrastructure – high-performance GPU hardware, cloud with C5 Type 1 attestation, GDPR-compliant processing, minimised maintenance and operating costs.
Why centron

From a mountain of documents to an answer

The knowledge is there – it’s just scattered. RAG systems make it searchable without sending it to third-party clouds.

Knowledge indexed

Documents from file repositories and wikis are migrated as embeddings to a vector database on NVMe volumes – the source files remain in S3.

Generated replies

A self-hosted language model generates responses with source citations – running on a dedicated GPU, accessible internally.

Internal matters remain internal

Contracts, manuals and project knowledge never leave your VPC – this is the key difference compared to cloud-based AI services.

Rights respected

Access rights from the source systems carry over into the search – everyone can only see what they are authorised to view.

Use cases

The advantages of AI-supported knowledge management

Retrieval-augmented generation (RAG) is an AI approach in which the language model, during execution, draws not only on its training knowledge but additionally uses information from a dedicated knowledge base – flexibly filled with your own documentation, for precise, context-related answers.

Automated data capture & organisation

AI captures and categorises information in real time – sources from repositories, wikis and drives become embeddings in the vector database, the originals sit in the AI data lake on S3 Object Storage.

Fast access to relevant content

AI-supported chatbots deliver answers with source references instantly, without manual searching – LLM inference runs on dedicated cloud GPUs with constant response times.

Personalised knowledge delivery

Information is tailored to employee roles and needs – access rights of the source systems carry through to the search, so everyone finds only what they are allowed to see.

Proactive knowledge distribution

Automatic identification and closing of knowledge gaps – the assistant recognises where documentation is missing or outdated and keeps corporate knowledge current.

Cost savings & optimised decision-making

Less manual effort for data maintenance and training – and well-founded, data-driven decisions through AI-supported analysis of your own knowledge base.

Effective onboarding & continuous learning

AI eases the onboarding of new employees with personalised training content and keeps knowledge up to date through automated updates.

Practical rather than pilot

Become an in-house knowledge assistant in a matter of weeks

Open-source components such as LangChain, Qdrant and vLLM integrate with the RAG stack on the centron infrastructure: an ingest pipeline in Kubernetes, a vector database on volumes, and inference on GPUs. The result: an in-house search and answer engine that the legal department can approve.

100 per cent in-houseRAG in your VPC · no data leakage
Calculate costs using the price calculator
  • Open building blocks – LangChain, Qdrant, vLLM and others
  • Sources linked – Folders, wikis, drives
  • Answer with supporting evidence – Source reference for each answer
  • Preservation of rights – Permissions remain in effect
Recommended modules

The right centron products

Customers typically implement this use case using these building blocks – which can be combined and expanded at any time.

Cloud GPU
Ab
92,59 € / Monat
NVIDIA performance
  • RTX A4000 from €92.59 per month
  • Quadro RTX 6000 from €170.83 · A100 from €489.47 · RTX 6000 Ada from €858.19 per month
  • Dedicated, not shared
  • No minimum term
Volumes
Ab
0,05 € / GB · Monat
NVMe Block Storage
  • Can be expanded whilst in operation
  • Snapshot-compatible
  • Independent of the VM
S3 Object Storage
Ab
5,00 € / Monat
Scalable storage
  • S3-compatible API
  • Free traffic
  • Unlimited scalability
In a nutshell

How much does AI-powered knowledge management cost at centron?

Knowledge management with AI: Make corporate knowledge searchable via RAG – on your own infrastructure, GDPR-compliant, with data remaining in-house. The core component is Cloud GPU from €92.59 per month – billed by the hour, with no minimum contract term. This is supplemented, as required, by Volumes and S3 Object Storage. Hosting is provided in compliance with the GDPR in centron’s own certified to ISO 27001 on the basis of IT-Grundschutz data centres, which hold BSI C5:2020 Type 1 certification. New accounts receive a €200 starting credit.

Packages and prices
Building blockPrice
Cloud GPUfrom €92.59 per month
Volumesfrom €0.05 per month
S3 Object Storagefrom €5.00 per month
AI & Compute FAQ

Frequently Asked Questions

Why should companies use AI for their knowledge management?

Companies face the challenge of capturing, organising and providing knowledge efficiently. AI automates these processes, speeds up access to relevant information and prevents knowledge loss. It thus increases productivity and improves decision-making.

What is a cloud GPU?

A cloud GPU is a graphics processing unit provided via the cloud that lets companies run compute-intensive tasks without their own physical hardware. Instead of running an expensive GPU locally, users access powerful computing capacity over the internet – at centron, a transparently communicated hourly usage fee applies. Using a cloud GPU is particularly advantageous for machine learning, 3D modelling, simulations, complex data analysis and the inference of large language models, as the computing power required scales flexibly and is used as needed.

How does our knowledge find its way into the system – and how is it kept up to date?

An ingest pipeline regularly reads from sources, parses documents and updates the embeddings – new documents can be queried after the next run. Everything runs within your VPC; deleted sources are also removed from the index.

What are some examples of configurations?

Configuration I: 8 cores, RTX A4000 (16 GB VRAM), 16 GB RAM, starting at, for example, with 500 GB storage – with inference: €146.23 per month (approx. €0.2031 per hour), without inference: €53.64 per month (approx. €0.0745 per hour). Configuration II: 16 cores, A100 (40 GB VRAM), 64 GB RAM, starting at, for example, with 500 GB storage – with inference: €602.79 per month (approx. €0.8372 per hour), without inference: €113.32 per month (approx. €0.1574 per hour). For a bespoke solution, please contact our sales team.

How much does it cost to get started?

The starting prices are deliberately low: Cloud GPU from €92.59 per month, volumes from €0.05 per GB per month and S3 Object Storage from €5.00 per month. New accounts receive a €200 starting credit valid for 60 days – you can calculate the cost of your specific configuration transparently using the price calculator.

Can this be implemented in a way that complies with the GDPR?

Yes – and that is the critical issue with AI-supported knowledge management: internal documents regularly contain personal data and trade secrets, which could fall into the wrong hands if an external AI service were used. With centron, the knowledge base, embeddings and model remain in Germany. The data centres are certified to ISO 27001 on the basis of IT-Grundschutz, with an unrestricted BSI C5:2020 Type 1 attestation for ccloud³ / Managed Cloud. Further details can be found in the Trust Centre.

Why is a BSI C5 attestation important for AI knowledge management?

AI-supported knowledge management frequently works with sensitive internal documents, processes and company data. The audit under the BSI C5:2020 Type 1 attestation confirms that our cloud has been audited against the BSI’s established criteria catalogue for secure cloud services. This gives companies a traceable basis for operating AI workloads with high requirements for security, transparency and compliance.

What advantages does object storage offer as a storage solution for AI applications?

Object storage is ideal for AI-supported knowledge systems with large datasets, as it processes big data flexibly, scalably and cost-efficiently. Training data, documents or databases can be stored without fixed folder structures and retrieved at any time. This makes object storage perfect for workloads that grow continuously. Compared with classic file systems, object storage enables particularly high resilience and simple integration into AI frameworks and pipelines. With centron S3 Object Storage, companies benefit from a GDPR-compliant, highly available storage solution with high-performance connectivity, designed for modern AI processes.

How does AI improve onboarding and learning in companies?

AI-supported knowledge management systems offer new employees personalised training content, provide relevant information and speed up onboarding. Through continuous learning and automated updates, corporate knowledge always stays up to date.

How transparent are the costs for centron cloud GPUs?

centron relies on a fair, transparent pricing model with a strong price-performance ratio: no hidden costs – you pay only for the performance used – and flexibility to adjust your GPU use to your needs at any time; all terms in the GPU pricing.

Can I rent servers from centron and which options are there?

Yes, you can rent various server solutions from centron that fit your requirements: virtual machines, quickly configurable and flexibly scalable, and managed servers with maintenance and operation by centron – you focus entirely on your work.

Get started for free

Sign up and receive €200 credit at centron within your first 60 days.

This promotional offer applies to new accounts only. Available exclusively to businesses.