01
Discovery and prioritisation
Rank use cases against value, data readiness, feasibility and the regulator whose expectations apply.
Solution · Sovereign AI Factory
A sovereign AI factory, from data to deployment
One delivery model for infrastructure, data readiness, model adaptation, deployment and operations — all inside Malaysia.
REF · SC-2026-FACTORY
Delivery · End-to-end Data · In-country Model · Adapted to your corpus Operations · Documented
Solution · Sovereign AI Factory
One delivery path from use case to operating model
A factory is not a building full of GPUs. It is the repeatable process that turns a priority use case into a governed production system: data prepared, model adapted, controls mapped, endpoint operated and quality measured.
Most AI programmes stall between the pilot and the operating model. The factory is a single accountable path across that gap, with explicit artefacts and acceptance gates at each stage.
- Discovery that prioritises use cases by value, feasibility and regulatory risk.
- Data readiness work before any fine-tuning begins.
- Model adaptation through RAG, LoRA or full fine-tuning as the use case requires.
- Deployment, evaluation and operating runbooks handed over together.
Capabilities
What the factory delivers
Six workstreams that can be contracted together or introduced in phases.
02
Data readiness
Inventory, classify, clean and govern the corpus before it reaches a training or retrieval pipeline.
03
Infrastructure
Provision in-country GPU capacity or design a private cluster sized to the selected workloads.
04
Model adaptation
Apply RAG, LoRA or full fine-tuning, with evaluation gates before any model is promoted.
05
Deployment
Expose the model through a governed endpoint with identity, network isolation and audit controls.
06
Operations and MLOps
Monitor quality, latency and cost; manage model versions, rollback and incident response.
Process
The five-stage delivery flow
Each stage has a defined output and an acceptance gate. Commercial commitments follow the evidence.
- 01
Discover
Produce a prioritised use-case portfolio, success metrics and a regulatory constraint map.
- 02
Prepare
Deliver a data-readiness assessment, access model and a corpus that is fit for the pilot.
- 03
Build
Stand up the infrastructure, retrieval pipeline and adapted model against agreed evaluation criteria.
- 04
Deploy
Harden, integrate identity and network controls, and pass the production acceptance review.
- 05
Operate
Run the service against a documented operating model, with quality and cost reviews on a set cadence.
Use cases
Where the factory is used
Sector patterns the delivery model is designed around. Each is scoped to the regulator and data class in play.
Financial services
Risk, compliance and customer-service workloads under BNM expectations and PDPA obligations.
Public sector
Citizen-service assistants and document workflows with in-country processing and audit trails.
Healthcare
Clinical documentation and retrieval under PHBPA and institutional ethics requirements.
Manufacturing
Quality inspection, maintenance knowledge and supply-chain analysis at the edge or in-country.
Controls
Sovereignty controls
The control baseline that applies across every factory workstream.
In-country data plane
Training data, model artefacts and inference traffic are designed to remain in Malaysia.
PDPA 2010 alignment
Data classification, retention and access controls map to Akta 709 obligations.
Immutable audit logs
Data access, model promotion and administrative actions are recorded and exportable.
Human accountability
Every stage has a named owner and an acceptance gate; high-risk outputs retain a human review step.
FAQ
Questions programme owners ask
How long does a factory engagement take?
It depends on scope, data readiness and the number of use cases. Discovery and a bounded pilot are scheduled first; production timing is agreed after the pilot acceptance review rather than promised on a sales page.
Who owns the adapted model and the data?
You do. Model weights, adapters, training data and evaluation artefacts remain your property. Bijak Cloud does not reuse them for other customers without written instruction.
Can the factory work with our existing cloud?
Yes. The data plane can be deployed in-country while integrating with an existing cloud for non-sensitive services. The boundary and transfer rules are documented in the design stage.
How do you handle regulatory expectations?
Each engagement starts with a constraint map covering PDPA 2010, the relevant sector regulator and your internal policy. We document how the design addresses each obligation; we do not claim a certification we do not hold.
Solution · Sovereign AI Factory
Start with one priority use case
Bring the use case, the data class and the regulator. We will map a discovery-to-pilot path with explicit acceptance gates.
Quotes are itemised by configuration, term and support. No fixed list price is published.