Question 1

What is Private LLM Deployment?

Accepted Answer

Run open-weight and managed models where your data lives. We build the gateway, guardrails and observability layer so every model call is governed, traced and cost-controlled.

Question 2

What does Lumino deliver as part of Private LLM Deployment?

Accepted Answer

Private VPC, on-prem & air-gapped, Open & managed model support, AI gateway with routing & fallbacks, Guardrails, PII redaction & policies, Tracing, evals & observability, CI/CD and versioning for models, Amazon Bedrock, Azure AI Foundry and Vertex AI in your own cloud account and GPU autoscaling and cost governance.

Question 3

Which technologies do you use for Private LLM Deployment?

Accepted Answer

Typical tools include Llama, Mistral, Qwen, Gemma, DeepSeek, Claude, GPT, Gemini, Kubernetes, KServe and Ray Serve — we choose the stack after reviewing your data, systems and constraints.

Question 4

What are common use cases for Private LLM Deployment?

Accepted Answer

BFSI private LLMs, Healthcare data residency and Government workloads. See our case studies for examples delivered in production.

Question 5

Do you offer Private LLM Deployment in USA, Canada, Singapore, UAE and India?

Accepted Answer

Yes. Lumino delivers ai infrastructure services to clients in USA, Canada, Singapore, UAE and India — as a fixed-scope project, time & materials, or a dedicated team.