What is private AI?
Private AI runs generative AI models inside an environment your company controls: on your own hardware, in a private cloud, or in a hybrid setup. Your documents and data are never sent to a public AI service and are never used to train someone else’s model.
How is Logic Sonata different from using ChatGPT at work?
Public AI tools process your prompts on infrastructure you do not control. Logic Sonata deploys the model, the knowledge base and the access controls inside your environment, so buyer data, costing files, contracts and source code stay under your governance with a full audit trail.
What does a Logic Sonata private AI solution include?
Everything needed to run AI privately: the hardware, the software and models, your company knowledge prepared as a secure knowledge base, access controls, implementation, staff training and ongoing managed support. One partner is accountable for the whole stack.
Do we need to buy GPU hardware?
No. Every product is available in three deployment models: hosted on managed private GPU cloud with no hardware purchase, on-premise on dedicated hardware inside your building, or hybrid, with on-premise for sensitive data and hosted for everything else.
What hardware do you deploy on-premise?
We are hardware-neutral and size the platform to your workload. Smaller teams often start with a compact AI workstation such as NVIDIA DGX Spark or an AMD Ryzen AI Max+ system, both of which offer up to 128 GB of unified memory in a desktop-sized unit. Larger rollouts use multi-GPU servers or a private cloud cluster.
Which countries do you serve?
Logic Sonata serves businesses in Singapore, Vietnam, Indonesia, Malaysia and Thailand, with delivery and support across Southeast Asia.
Which industries do you work with?
Manufacturers, retailers, design companies, suppliers and regional business groups are our core customers. In practice, any company that wants to use AI while keeping its data private is a good fit.
How long does a private AI pilot take?
Most customers start with an AI Privacy and Readiness Assessment, which produces a 30/60/90-day roadmap. The pilot then covers one working use case, so you prove value with real users before committing to a full rollout.
How does ongoing support work?
Every deployment moves into a managed support tier sized to your users and how critical the system is, from monthly health checks to a dedicated technical lead with a custom service level. We recommend the right tier during the assessment.
