Responsible AI
Governed accessEdrak provides a controlled environment for accessing AI models, rather than unmanaged use across disconnected tools.
Safeguards against misuseEdrak applies platform safeguards and usage restrictions designed to reduce abuse, security risks, and harmful uses.
Human accountabilityCustomers remain responsible for how they use the platform, how they review outputs, and how AI is applied in consequential decisions.
Clear limitsAI outputs can be incomplete, inaccurate, or unsuitable for a particular purpose. They should be reviewed before being relied on.
Enterprise oversightEdrak gives organizations administrative visibility and controls to support internal governance, policy enforcement, and responsible deployment.
Our approachResponsible AI at Edrak is grounded in a practical principle: AI should support human work, not replace human judgment where judgment matters.We design the platform to help organizations use AI in a way that is:UsefulAI should deliver real value in workflows where speed, scale, and productivity matter.
ControlledUse of AI should take place within a managed environment with visibility, permissions, and operational safeguards.
ReviewableOutputs should be capable of being reviewed, challenged, and validated by the people using them.
AccountableOrganizations and users remain responsible for the decisions they make, including decisions informed by AI outputs.
What responsible use means in practiceEdrak is built to support responsible enterprise use of AI, not unrestricted experimentation without oversight.In practice, that means:- Access to AI takes place through a governed platform layer
- Organizations can manage users, permissions, and workspace activity
- Safeguards are in place to help prevent misuse or abuse
- Customers are expected to review outputs before relying on them
- High-impact uses require human judgment and appropriate internal controls
- Incomplete
- Inaccurate
- Misleading
- Out of date
- Unsuitable for a specific operational, legal, financial, or regulatory use case
- Access controls and permission structures
- Monitoring for misuse, abuse, or suspicious activity
- Restrictions on attempts to bypass safeguards
- Restrictions on harmful or prohibited use cases
- Enforcement actions where needed to protect customers, the platform, or legal compliance
- Defined approval processes
- Human review before action
- Clear accountability for final decisions
- Restricted access where appropriate
- Internal policies on acceptable and unacceptable use
- Centralize how AI tools are accessed
- Apply governance across multiple providers
- Maintain visibility into usage
- Reduce unmanaged use of external tools
- Introduce AI in a more structured and reviewable way
- Fraud or deception
- Malware or cyber abuse
- Spam or abusive automation
- Circumvention of safeguards or restrictions
- Development of competing models through unauthorized use of inputs or outputs
- Other unlawful, harmful, or abusive activity
- The platform's role as a governance layer
- Core safeguards and restrictions
- Data handling boundaries
- Customer responsibilities
- Contractual commitments relating to platform use
- Providing a controlled platform environment
- Implementing safeguards and platform integrity controls
- Supporting visibility, permissions, and oversight
- Maintaining contractual and policy boundaries for use of the service
- Defining internal AI usage policies
- Managing user access and approval structures
- Reviewing outputs before reliance
- Determining whether specific use cases are appropriate
- Ensuring their use complies with applicable laws, regulations, and internal requirements
- Powerful AI should be available in a governed environment
- Customers should have visibility and control
- Safeguards should be built into the platform
- High-impact uses should remain subject to human review
- Responsibility for decisions should remain with people and organizations, not with generated outputs