Evaluation framework for AI modelling 
 
Validating AI models before integrating them into products is crucial to ensure they are reliable, safe, and aligned with user expectations. Unvalidated models can lead to errors, biased outcomes, or unpredictable behaviour, which can undermine user trust and compromise product integrity. Thorough validation helps identify potential risks, ensures compliance with ethical and regulatory standards, and confirms that the model performs well across diverse real-world conditions. This step is vital for delivering high-quality, responsible AI-driven products that users can depend on.
 
What to expect:
This service offering from the Insight Research Centre for Data Analytics is built upon our expertise in validating AI pipelines in public and private domains. Model validation is a crucial step in the deployment and operationalisation of AI for commercial entities before deployment.
 
The service consists of three elements to help you develop your data engineering roadmap:
1-to-1 Strategy Clinic (1-hour online session)
Understand your objectives and vision.
Align the roadmap with your specific needs.
User-Centred Design Process (9 x 1-hour meetings over 2 months) 
Facilitate the design of a model deployment pipeline. 
Ensure the solution is tailored to user needs and operational requirements. 
Evaluation & Piloting Support (1-hour online session) 
Follow-up consultation to define the evaluation framework and pilot strategy.