AI Infrastructure, Engineered for Production
Cloud Ape designs and operates the “heavy metal” underneath modern AI — the bare-metal GPU clusters, serving layers, and MLOps pipelines that turn foundation models into dependable, production-grade workloads. We work across GCP and Azure, and specialize in on-prem and sovereign AI for organizations that cannot send data off-site.
GPU & Compute Infrastructure
Bare-metal NVIDIA DGX systems, GPU Operators, and high-throughput storage for distributed training and inference. We tune the full stack — networking, storage, and scheduling — so your GPUs run at utilization, not idle.
LLM Serving & Inference
High-throughput model serving with vLLM and open-weight models hosted in your own environment. Whether you need low-latency chat, batch inference, or multi-tenant serving, we design it for cost, throughput, and security.
RAG & Vector Search
Retrieval-augmented generation pipelines backed by Qdrant — grounding models in your data instead of generic training data. We build the ingestion, embedding, and retrieval layers so answers stay accurate and auditable.
Agentic Systems
Secure, locally-hosted autonomous coding agents built on open-weight models — accelerating engineering workflows without sending your code or data off-site.
MLOps, GitOps & Observability
Declarative, multi-tenant Kubernetes managed through ArgoCD, with the LGTM stack (Loki, Grafana, Tempo, Mimir) for platform health and GPU-utilization metrics. Every model, pipeline, and cluster change is versioned, reviewed, and reversible.
Managed AI Services
Google Cloud Vertex AI and AutoML integration for teams that prefer managed tooling over self-hosted infrastructure.
Compliance by Design
For Swedish and European enterprises, we build with GDPR, EU AI Act, and data-residency requirements from day one — sovereign AI that stays inside your jurisdiction.