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In today’s AI-driven world, governing machine learning (ML) models is a critical challenge for organizations. Data Ninjas offers a custom solution, leveraging Collibra and other advanced tools, to ensure AI and ML models are transparent, trustworthy, and compliant. Our solution addresses the need for effective oversight in model lifecycle management while fostering responsible AI practices.
The need for AI & ML governance arises from the complexities of managing models throughout their lifecycle—from development and deployment to monitoring and retirement. Without proper governance, organizations risk facing issues like model bias, regulatory non-compliance, lack of accountability, and data integrity problems. Our solution is designed to provide end-to-end oversight, helping organizations mitigate these risks while fostering a culture of responsible AI use.
Our solution begins with a thorough assessment of your current AI and ML governance framework. Data Ninjas evaluates your model lifecycle, compliance requirements, and existing tools to identify gaps and opportunities. This phase includes mapping data lineage, auditing workflows, and understanding stakeholder needs to create a tailored governance strategy.
We implement a comprehensive governance framework by integrating Collibra with advanced monitoring and automation tools. This includes setting up metadata management, role-based access controls, and automated workflows for streamlined operations. Our approach ensures a seamless rollout while minimizing disruptions, enabling teams to adopt the solution with ease.
AI and ML governance is an evolving process. Our solution includes ongoing monitoring and updates to ensure models remain compliant and effective. We provide analytics to track performance, identify potential risks, and recommend enhancements, helping your organization stay aligned with regulatory changes and business goals.
Our Solution at a Glance
Partner with Data Ninjas to simplify AI & ML governance while maximizing the impact of your AI initiatives. Contact us today to discover how we can help your organization stay ahead.
Extensible operating model tailored for ML lifecycle data assets.
Predefined relationships between ML assets for complete data lineage and traceability.
Workflows for model approval and production deployment.
Tracking of datasets, feature management, and their impact on model effectiveness.
Centralized metadata management within a model registry.
Metadata ingestion from external ML libraries with custom ingestor support.
Defined processes for ML data lineage, including external data sources.
MLNinja creates a top down operational model to deal with most ML lifecycles. The fully extensible model creates new data assets and relationships allowing full data lineage with total transparency. This allows governing and tracking all ML changes over an extended period of time with historical audit capability.
Data Ninjas Compliance Team
Data Ninjas Compliance Team
Data Ninjas Compliance Team
Data Ninjas Compliance Team
Regardless of the data governance you choose, we will deliver sustainable results for you!
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