Q1
What is a Self-Hosted LLM?
A self-hosted LLM is a Large Language Model deployed on infrastructure controlled by your organisation rather than being hosted entirely by a public AI provider.
It allows businesses to run open-source LLMs on their own server or private infrastructure.
Q2
Do you provide the server for the LLM?
No. Your company provides the server or computing infrastructure.
We provide the LLM installation, configuration and deployment service.
Q3
Can you install an open-source LLM on our existing server?
Yes. We can first assess your existing server hardware and determine whether it is suitable for your intended LLM and workload.
The required hardware depends on the model, quantisation, number of users and expected workload.
Q4
Can a Self-Hosted LLM run without the internet?
Some self-hosted LLM deployments can operate within a private or isolated environment after the required software and model files have been installed.
The exact setup depends on your infrastructure, security requirements and intended integrations.
Q5
Is a Self-Hosted LLM more secure than ChatGPT?
Not automatically.
Self-hosting gives your organisation greater control over infrastructure and data processing, but security still depends on how the server, network, authentication, software and AI environment are configured and maintained.
Q6
Is Self-Hosted AI suitable for Malaysian businesses?
It can be, especially for businesses that need greater control over AI processing, internal data or infrastructure.
The suitability depends on your business requirements, available hardware, security policies and intended AI applications.
Q7
Can we use our company documents with a Self-Hosted LLM?
Yes. A self-hosted LLM can be combined with technologies such as Retrieval-Augmented Generation (RAG) to create AI applications that work with your company’s internal documents and knowledge sources.
The document storage, retrieval and access-control architecture should be designed according to your requirements.
Q8
What Open Source LLM can you install?
The suitable model depends on your hardware and use case.
Different open-source and openly available LLMs have different requirements for memory, processing power, speed and capabilities.
We can help you evaluate the appropriate option instead of choosing a model based only on its parameter size.
Q9
Do I need a GPU server to run an LLM?
Not always.
Some smaller LLMs can run on CPU-based systems, while larger models generally benefit from more powerful GPUs or other suitable acceleration hardware.
We can assess your existing infrastructure and recommend a practical deployment approach.
Q10
Can you help us build more than just the LLM?
Yes.
The self-hosted LLM can be the foundation for additional AI solutions such as private RAG, internal AI assistants, document intelligence, workflow automation and AI agents.
We can help you identify the next step based on your business requirements.