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Service

GenAI Infrastructure & Deployment

Own your AI stack. Run models on your terms.

Not every organization wants to depend on OpenAI or Google APIs. We design and deploy private LLM infrastructure, on-premise GPU clusters or cloud-based, so you control your models, costs, and data. We run our own GPU inference infrastructure, so the setups we recommend are ones we operate every day.

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What we deliver

GenAI Infrastructure & Deployment services

  • Private LLM Deployment

    Deploy open-source models (Llama, Mistral, Qwen, and others) on your own hardware or cloud VPC.

  • LLM Fine-tuning

    Adapt a foundation model to your domain, terminology, and tasks using your own data.

  • Cloud AI Architecture (AWS / GCP)

    Design and implementation of production AI infrastructure on AWS or GCP.

  • MLOps & AI Observability

    Monitoring, evaluation pipelines, and quality metrics for deployed AI systems.

Best for

Organizations that need cost control, data sovereignty, or performance beyond what SaaS AI APIs offer.

Case studies

Related project

Private GPU Inference Infrastructure

Client: Internal project, Trilagi

Challenge
Developing and evaluating AI for IT operations meant running and fine-tuning open-source LLMs on sensitive data, with predictable cost and without depending on external model APIs.
What we built
On-premise GPU infrastructure built on production-grade NVIDIA data-center GPUs and AMD EPYC platforms, serving open-source LLMs for inference and supporting fine-tuning workloads.
Result
Full control over models, data and cost, plus a reference architecture for private LLM deployments that we use every day.

“We wanted AI without handing our data and our costs to a single API provider. Models run where it makes sense for us, and the costs stay predictable.”

CTO, Qlos

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Contact

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