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On-Premise AI Solutions

Run open-weight language models on hardware you control. We handle GPU sizing, inference serving and network isolation, so sensitive data stays inside your perimeter and your auditors get a straight answer.

  • Your Hardware, Your Data
  • Runs Fully Offline
  • Data Stays in Sweden

Why On-Premise AI?

Data Sovereignty & Compliance

Some data cannot go to a cloud API. Defense material, patient records, bank transactions. If your legal team has already said no to cloud AI, the question is not whether to run models on your own infrastructure but how to do it well.

  • Defense sector requirements and säkerhetsskyddslagen
  • Patient data under Patientdatalagen and GDPR
  • Financial data under PSD2 and MiFID II
  • Government and municipal records

Nothing Leaves Your Network

Prompts, documents and model weights stay on your machines. No external API calls, no vendor telemetry, no training on your data. For air-gapped setups we design and document how outbound connectivity, telemetry, model updates and support access are controlled, so the isolation is verifiable at the network level rather than asserted.

  • Air-gapped deployment where the classification demands it
  • Runs with no internet connectivity at all
  • Every request logged for audit
  • Network isolation with VLANs and firewall zones

Organizations That Need On-Premise AI

  1. Government & Defense

    Classified material does not touch a public cloud. We build AI environments that survive a security review: isolated networks, controlled hardware, documented data flows.

    Examples: Intelligence analysis, defense logistics, secure communications, threat detection, classified document processing

  2. Healthcare & Life Sciences

    Patientdatalagen and GDPR set hard limits on where patient data may be processed. An on-premise model can read the journal without the journal ever leaving the hospital.

    Examples: Clinical decision support, medical imaging analysis, drug discovery, patient record analysis, research data processing

  3. Financial Services

    Banking secrecy and PSD2 do not bend for a convenient API. Fraud models and document analysis run next to the data, inside the security perimeter you already defend.

    Examples: Fraud detection, credit risk analysis, trading algorithms, KYC/AML screening, financial document analysis

Our On-Premise AI Services

Private LLM Deployment

  • Llama 4 (Scout / Maverick)
  • Mistral Medium 3.5 (open weight)
  • OpenAI gpt-oss (120B / 20B)
  • DeepSeek V4 & GLM-5.2
  • Fine-tuning on your own data
  • Models with strong Swedish support
  • Quantization (GPTQ/AWQ) to fit your GPUs

Infrastructure Setup

  • GPU cluster design (NVIDIA H100/H200/B200)
  • Kubernetes orchestration
  • Load balancing & auto-scaling
  • Storage architecture (NVMe/SAN)
  • Network optimization (InfiniBand)
  • Backup & disaster recovery
  • High availability with automatic failover

Integration & APIs

  • OpenAI- and Anthropic-compatible APIs
  • Custom REST/GraphQL APIs
  • SDK development (Python/TypeScript)
  • Integration with your internal applications
  • Connectors for legacy systems
  • Authentication (LDAP/AD/SAML)
  • API gateway & rate limiting

Security & Compliance

  • Network segmentation & VLANs
  • Encryption at rest & in transit
  • Role-based access control (RBAC)
  • Audit logging & SIEM integration
  • Penetration testing
  • Compliance documentation for your auditors
  • Hardening against CIS benchmarks

Data & RAG Solutions

  • Vector databases (pgvector, Qdrant, Milvus)
  • Document ingestion pipelines
  • Embedding generation on local GPUs
  • Semantic search over your documents
  • Knowledge graph integration
  • Retention policies you define
  • Backup & versioning of indexes

Operations & Support

  • Monitoring & alerting around the clock
  • Performance tuning as load grows
  • Model updates & security patching
  • Capacity planning before you run out
  • Incident response
  • Training your team to run it themselves
  • Managed service if you would rather not

Technology Stack

LLM Models

  • Llama 4 (Meta)
  • Mistral Medium 3.5
  • OpenAI gpt-oss
  • DeepSeek V4 / GLM-5.2

Inference & Serving

  • vLLM
  • TGI (Text Generation Inference)
  • TensorRT-LLM
  • Triton Inference Server

Orchestration

  • Kubernetes
  • Docker
  • Helm Charts
  • ArgoCD (GitOps)

Hardware

  • NVIDIA H100 / H200
  • NVIDIA B200
  • AMD MI300X / MI325X
  • InfiniBand networking

Vector Databases

  • Qdrant
  • Milvus
  • Weaviate
  • pgvector (PostgreSQL)

Monitoring

  • Prometheus
  • Grafana
  • Elasticsearch/Kibana
  • Nvidia DCGM

Security

  • Vault (HashiCorp)
  • cert-manager
  • Falco (runtime security)
  • Trivy (vulnerability scanning)

Development

  • LangChain
  • LlamaIndex
  • Hugging Face Transformers
  • FastAPI/Python

Ready to Run AI on Your Own Hardware?

Book a technical call. Bring your security requirements and rough usage volumes; we will sketch an architecture, suggest models and hardware, and give you an honest view of cost and effort.

Schedule Technical Consultation