Winning Team Featured On
The Need to Deliver Trusted AI has Never Been Greater
Common Challenges in Delivering Trusted AI
AI can end up being a ‘black box’ for organizations
Many businesses fail to move from experimental AI into value
Only 15
Of leading enterprises have deployed AI capabilities into production at any scale.
The need to deliver Trusted AI has never been greater
- Understandability
- Fairness
- Traceability
- Auditability
- Teachability
Trusted AI Confidence
- Customers trust your organization
- Elimination of racial discrimination in use cases such as facial recognition
- Ensure organizations embrace ethical AI and fair ML models
I think this might be the best path to safety, in the sense that an AI that cares about understanding the universe, it is unlikely to annihilate humans because we are an interesting part of the universe,”
Elon MuskBest practice Governance
- Gives the Trusted AI lenses to the Chief Compliance/Risk Officer
- Centralized governance with transparent auditing of ML models
- Prevents reputational damage caused by failure to comply with regulations
As a Black woman in tech, I understand the harsh realities of what happens. Technology serves as a mirror for our society. It reveals our bias, it reveals our discrimination, [and] it reveals our racism.”
Rashida HodgeThe Trusted AI Advantage
- Minimize risk with enterprise-grade security and governance across all data, models, and infrastructure.
- Access advanced reporting and monitoring tools to improve performance, compliance, and auditability.
Our Solution is Trusted AI
Feature Highlights
Bias and Fairness
Detecting Bias via Fairness Metics & Solving Racial Discrimination for models in production
Humility Rules
Provide guardrails that ensure predictions are within the normal range
Prediction Explanations
Allows you to calculate the impact of a configurable number of features (the “reasons”) for each outcome your model generates
Uncompromising Trust & Security
- Privacy: Ability to use company’s existing data in their own cloud without worrying about IP / Copyright infringement, data leakage, etc
- Security: Secure integrations with other enterprise tools, sources of data, and other AIs.
- Compliance: Easy audits for legal and IT compliance.
- Trust: Companies can set policies and guardrails to ensure each employees’ AI behaves as desired.
- Zero Knowledge Training: With an easy to use interface, companies can train on proprietary data in their own cloud with zero visibility to Trusted AI or other third parties.
ML Model Governance
Feature Highlights
Approval workflow
Maintain thorough reviews of model updates with less tedious manual work using customizable review cycles and approval workflows.
Audit trail
Complete audit trail captured to explain model lineage and history. System automatically records all events, any model changes applied and all reviewers involved.
Security built-in
Import existing IT security policies for users and groups. Share deployments with role based access control.
