Services

One team across strategy, build, assurance, and operations.

Ordinexis provides the operating model, engineering, controls, infrastructure, and ongoing support required to move enterprise AI from a defined business case into production.

Engagement scopeAdvisory and architecture
Software and model engineering
Infrastructure and integration
Assurance and managed operations

Service portfolio

AI strategy and operating model

Prioritisation, business-case definition, control design, architecture, procurement support, and a sequenced path from evaluation to production.

Opportunity portfolio, risk register, target architecture, delivery roadmap

Custom AI software development

Intelligent automation, predictive analytics, decision support, recommendations, and AI capabilities integrated into existing applications and workflows.

Production applications, APIs, workflow integrations, evaluation suites

Private LLM and retrieval systems

Domain-specific language systems, governed RAG, model fine-tuning, quantisation, distillation, evaluation, and Bahasa Malaysia NLP.

Knowledge assistants, private models, source controls, audit logs

Vision, voice, and multimodal AI

Camera intelligence, object detection, document AI, quality inspection, voice bots, transcription, sentiment analysis, and multilingual interaction.

Monitoring systems, contact-centre automation, document workflows

Private GPU infrastructure

NVIDIA H200 cluster design, Linux GPU operations, model serving, edge inference, and dedicated, air-gapped, hybrid, or on-premise deployment.

Sizing, build, deployment, monitoring, managed inference operations

AI assurance and governance

Model risk assessment, adversarial and red-team testing, LLM threat review, code review, penetration testing support, policy, and human-control design.

Assurance findings, control framework, test evidence, remediation plan

Delivery model

Defined gates from use case to production.

Each stage creates evidence for a go, revise, or stop decision. This keeps technical work connected to operating value and risk ownership.

Frame

Workflow, users, value, constraints, baseline, and accountable owners.

Validate

Data readiness, architecture, controls, evaluation criteria, and proof of value.

Deploy

Integration, security review, user acceptance, operational readiness, and change support.

Operate

Monitoring, model evaluation, incident handling, optimisation, and governance review.

Deployment follows the organisation's constraints.

We support public cloud, private cloud, on-premise, dedicated, hybrid, edge, and air-gapped patterns. The choice is driven by data classification, latency, resilience, control, and total operating cost.

Start with the business problem and the operating constraints.

We will map a practical route from evaluation to a governed production system.

Schedule a briefing