AI GOVERNANCE

Business value with governed data and ethical AI

The new challenge for everyone who wants to get started with AI are the Guidelines and Regulations on Data- and AI Ethics being implemented across the globe.

ETHICAL AND TRUSTWORTHY AI

ETHICAL & UNBIASED AI

Ethical AI is structured around principles such as fairness and algorithmic bias.

robust and traceable AI

ROBUST & TRANSPARENT AI

Full traceability of all data and model events is secured across the platform.

full set of Governance requirements for data and AI model development

EXPLAINABLE AI

Before everything else, ethical AI is human-centered. So besides model performance, it ensures explainable AI models.

AI Governance - Action Tracking

Action tracking

Advanced metadata and meta-event tracking-technology tracking all events.

Grace AI Governance - Dashboarding

Dashboarding

Configurable dashboards to monitor workflows, models, IT infrastructure and more.

AI Governance - Dashboarding
Grace AI Governance - Relationships
AI Governance - Relationships between events

Relationships

Detailed analysis of the relationships between all events.

Ethical AI in the Grace Enterprise AI Platform

The process of AI model Development, Deployment and Operation includes comprehensive reporting to external and internal stakeholders to ensure governance in real-time and deliver ad-hoc information to IT and Businesses.

Verifiable transparency

The core behind 2021.AI’s Ethical AI technological approach is metadata and meta events. We offer full transparency, with verifiable proof – reports and audits.

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METADATA / METAEVENT

 Immutably logging of everything that happens in the AI model lifecycle, from data ingest to final operation of the model in production.

EXPLAINABILITY

We run different checks to make sure explainability requirements have been met and make sure they have been taken under consideration.

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VALIDATIONS AND CERTIFICATIONS

Validations and certifications are the way to ensure legislations have been followed before models can be deployed.

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TRANSPARENCY

Validating that, for example, a bias or anonymization test or process has been executed in the AI development process.

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REPORTING

Reports offer an easy export solution for stakeholders to validate and audit exceptions.

AUDITS

The final frontier of a legislator’s ability to verify that AI has been developed, deployed, and operated in compliance with the regulation.

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