Private LLM deployment, AI agent development, and dedicated GPU infrastructure. Operated on owned hardware in EU jurisdiction. No third-party API exposure. No shared compute.
Every inference call to a third-party AI API is a data transfer. Your documents, records, and queries are processed on hardware you don't control. For regulated industries or data-sensitive operations, this is an unacceptable architectural dependency.
Zubra deploys model weights, inference servers, and API endpoints entirely within your infrastructure perimeter. Model selection, quantization, fine-tuning, and RAG pipelines are managed by us. We handle the full stack. Your data never leaves your environment.
GPU infrastructure in Ljubljana, EU jurisdiction, with OpenAI-compatible endpoints your team can adopt without rewriting application code.
From model deployment to full multi-agent systems. We cover the entire AI stack on private infrastructure.
We deploy and operate large language models (Llama, Mistral, Falcon, and domain-specific variants) on dedicated hardware. Model weights, inference servers, and API endpoints reside entirely within your infrastructure. OpenAI-compatible endpoints, no rewrite required.
Purpose-built autonomous agents scoped to your specific workflows, not generic assistants. Each agent is designed to execute discrete tasks, integrate with your internal tools and APIs, and operate within defined decision boundaries. Applied to automating knowledge-intensive work, multi-step processes, and document-processing at scale.
Networks of specialised agents, each scoped to a single function, exchanging context and outputs to execute workflows that no individual model can complete alone. Deployed across due diligence automation, competitive intelligence pipelines, code review, and autonomous research operations.
Dedicated GPU servers configured for AI inference, fine-tuning, and data processing. Predictable performance, defined SLAs, and pricing that reflects your actual workload, not spot market volatility. For AI product teams and research organisations that require dedicated compute without public cloud dependency.
Every AI engagement is scoped to the specific needs of the organisation. No standard packages, no predetermined stack. We begin with your constraints: data environment, compliance requirements, existing infrastructure, and target workflows.
Model selection, hardware configuration, deployment architecture, and integration design are determined by what your use case actually demands. Whether that's a lightweight inference setup for a single internal tool or a multi-model agent system processing high-volume enterprise data, the solution is defined by your requirements, not by what we have off the shelf.
We work closely with your technical team throughout scoping, deployment, and ongoing operation to ensure the system performs as designed in your specific environment.
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