Private AI Deployment
Local and private large-language-model deployment on client premises or on Group infrastructure in Malaysia — from model selection and optimisation through to operations.
From evaluation to operated platform
A structured engagement for organisations that need the capability of modern language models without sending data to a third-party service.
Use-case and data assessment
Which workloads justify a private deployment, what data they touch, and what the regulatory position requires.
Model selection and optimisation
Evaluation of open-weight models against the client’s tasks; quantisation, fine-tuning and retrieval design to meet accuracy and latency targets on the available hardware.
Infrastructure
Sizing and provisioning on client hardware or Packet Cloud Services compute in Malaysia, with PacketX as the governed access layer.
Operations and governance
Monitoring, model updates, access control and the audit evidence a compliance function needs — operated by Packet Labs or handed over with training from Packet Academy.
When a private deployment is the right answer
Data sovereignty
Personal, financial, clinical or classified data that cannot leave the jurisdiction or the organisation.
Predictable cost at volume
High-volume document and transcription workloads where per-token pricing does not scale.
Auditability
Regulators and internal audit that require the model, its inputs and its outputs to be inspectable.
Scope a private deployment
An assessment of your workloads, data and infrastructure, with a recommended architecture.