Build Reliable & Powerful ML models
About VDML
Background
AI doesn’t always get it right. Managing risk, governance, compliance, accuracy and performance through KJR’s Validation Driven Machine Learning can help your organisation deploy AI with confidence.
VDML (Validation Driven Machine Learning) is a methodology developed by KJR to guide customers in their development of robust and reliable Machine Learning models to deliver AI solutions.
Our Approach
VDML addresses unique challenges and uncertainties in systems employing ML. VDML emphasises understanding the limitations of both models and data, and uses iterative validation methods to guide and assess ML model behaviour.
VDML integrates with ModelOps and DataOps workflows, enabling a seamless integration of ML validation activities into an agile, CI/CD, and DevSecOps methodology. It adopts a data-centric AI approach, iteratively evaluating the performance of models drawn upon target data domains.
VDML SERVICES
- AI Verification / Test & Evaluation
- AI Trust, Governance, Risk and Security Management
- Data augmentation / Data generation
- Market Surveillance