05
Tech Infrastructure

Technology Capability Review

• Evaluate current technology and data capabilities using structured frameworks.
• Conduct maturity surveys and stakeholder interviews to identify gaps, risks and alignment opportunities.

Advanced Data Architecture Design

• Design hybrid data systems that handle structured, semi-structured and unstructured data.
• Recommend modular pipelines and feature stores to automate ingestion, transformation and consistency for model training and inference.
• Recommend advanced modelling techniques (vector databases, schema-on-read) and define integration strategies to optimise efficiency and enable future scalability.

Data Governance and Risk Management

• Establish governance frameworks covering ownership, quality control, lineage tracking and compliance.
• Conduct risk assessments addressing security, model bias and operational resilience.

Infrastructure Scalability and Security

• Advise on deployment models (cloud, on-premise or hybrid deployment models) to meet latency, sovereignty, and scale requirements.
• Recommend orchestration and MLOps platforms (e.g., Kubernetes, SageMaker) for secure, scalable operations.

Frameworks and Tools for Execution

• Employ AI diagnostic surveys, maturity models, and gap analyses to prioritise initiatives.
• Recommend/prototype monitoring dashboards and metadata management to ensure transparency, reproducibility and operational stability.