TechShift
TechShift
Support & Guidance
Clear answers to the most common questions about AI transformation, implementation timelines, costs, and governance.
Most roadmap engagements take between 6 and 12 weeks, depending on the complexity of the organization and the number of business units involved.
An AI strategy defines the 'why' and the 'what' (business value and use cases), while a technology roadmap defines the 'how' (infrastructure, platforms, and tools required to deliver that value).
No. In fact, starting the strategy first helps identify which data assets are actually valuable, allowing you to prioritize data remediation efforts where they will have the most impact.
Yes. Most of our work involves connecting modern AI models to legacy systems like SAP, Oracle, and Microsoft Dynamics through custom middleware or API wrappers.
We follow a 'security-by-design' approach. We deploy air-gapped models or VPC-isolated environments to ensure your sensitive enterprise data never leaves your controlled infrastructure.
Our SME engagements are structured as fixed-price 6-week sprints, typically ranging from RM40K to RM120K depending on scope. 50-70% of this can often be offset by MDEC MDAG-AI or SME Digitalisation grants.
The primary vehicle is the MDEC MDAG-AI grant (up to RM2M). Additionally, the SME Digitalisation Grant (RM5,000) and the GITA 60% tax deduction for automation are applicable.
MLOps (Machine Learning Operations) is a set of practices that aims to deploy and maintain machine learning models in production reliably and efficiently. Without it, models often remain as experimental scripts that are difficult to scale or monitor.
While PDPA covers general data privacy, AI governance addresses specific algorithmic risks such as bias, explainability, and automated decision-making transparency that are not fully covered by standard privacy laws.
Every organization is unique. Schedule a 30-minute discovery call with our strategy team to discuss your specific transformation challenges.