[OK] Private AI infrastructure for Malaysian enterprises.

Large Language Model (LLM) and Retrieval-Augmented Generation (RAG) services that run on infrastructure you control — your own data centre, a Malaysian private cloud, or a fully air-gapped network. Documents and prompts stay within your environment, designed to support PDPA compliance.

STATUS: CHECKING… DEPLOY: ON-PREMISE · PRIVATE CLOUD · AIR-GAPPED LANGUAGES: BAHASA MELAYU · ENGLISH

> SYSTEM_CAPABILITIES

01 // DATA_SOVEREIGNTY

Your data stays in your environment

Documents, prompts and answers are processed on servers you control. No third-party AI provider sees your data. Deploy on-premise, in a Malaysian data centre, or air-gapped.

02 // ARCHITECTURE

Local RAG & vector search

Connect internal policies, manuals and document repositories to a local vector database (e.g. Qdrant) with multilingual search and re-ranking for grounded, source-cited answers.

03 // INTEGRATION

Streaming REST API for your systems

Gemini-style endpoints with streaming (SSE), one API key per system, project-level data isolation, audit logs and usage reporting — ready to plug into existing applications.

04 // COST_CONTROL

Predictable infrastructure costs

No per-token cloud billing or surprise API price changes. Start on CPU servers and scale to dedicated GPUs when you need faster responses.

// Sample API request

curl -N -X POST \
  "https://api.zetacoreai.cloud/api/v1/profiles/<profile>/knowledge:streamGenerateContent?alt=sse" \
  -H "Authorization: Bearer <PROFILE_API_KEY>" \
  -H "Content-Type: application/json" \
  -d '{
    "profile": "<profile>",
    "contents": [{"role": "user", "parts": [{"text": "What is our leave application procedure?"}]}]
  }'

Ready to deploy secure AI on your infrastructure?

Talk to our solutions team about deployment options and hardware sizing for your workload.

Get in touch @ zetasb.com.my