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Founder's Pitch
"AI Trust OS offers a continuous, telemetry-driven governance framework for autonomous AI observability and zero-trust compliance in enterprises."
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0-10 scaleHigh Potential
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Why It Matters
As organizations increasingly use AI, ensuring governance and compliance becomes critical to meet regulatory and security standards.
Product Angle
Develop AI Trust OS into a SaaS compliance monitoring tool that integrates with existing observability solutions to provide real-time compliance status and risk alerts.
Disruption
AI Trust OS could replace manual compliance processes and outdated governance software that can't adapt to dynamic, AI-driven environments.
Product Opportunity
As AI adoption grows, enterprises face compliance challenges. Providing real-time governance tools might attract large enterprises that need to maintain compliance with regulations like GDPR and the EU AI Act.
Use Case Idea
An enterprise-level compliance tool that automatically discovers and monitors AI systems to ensure they meet regulatory standards and maintain operational integrity.
Science
The paper proposes a framework called AI Trust OS that shifts traditional compliance from manual tracking to a machine-driven, continuous observability and zero-trust model. It uses telemetry to autonomously discover and validate AI systems, leveraging existing observability data while operating within a zero-trust environment.
Method & Eval
The framework was outlined conceptually and applied to principles of zero-trust and AI observability. However, there are no concrete benchmarks or performance results shared.
Caveats
The system is conceptual without detailed prototyping or demonstration of efficacy. Dependence on existing telemetry data quality could limit its functionality.
Author Intelligence
Eranga Bandara
Old Dominion University, Norfolk, VA, USA
cmedawer@odu.edu
Asanga Gunaratna
AI Motion Labs, Melbourne, Australia
founders@complianceoslab.app
Ross Gore
Old Dominion University, Norfolk, VA, USA
rgore@odu.edu
Abdul Rahman
Deloitte & Touche LLP, USA
abdulrahman@deloitte.com
Ravi Mukkamala
Old Dominion University, Norfolk, VA, USA
mukka@odu.edu
Sachin Shetty
Old Dominion University, Norfolk, VA, USA
sshetty@odu.edu
Sachini Rajapakse
IcicleLabs.AI
sachini.rajapakse@iciclelabs.ai
Isurunima Kularathna
IcicleLabs.AI
isurunima.kularathna@iciclelabs.ai
Peter Foytik
Old Dominion University, Norfolk, VA, USA
pfoytik@odu.edu
Safdar H. Bouk
Old Dominion University, Norfolk, VA, USA
sbouk@odu.edu
Xueping Liang
Florida International University, USA
xuliang@fiu.edu
Amin Hass
Accenture Technology Labs, Arlington, VA, USA
amin.hassanzadeh@accenture.com
Ng Wee Keong
Nanyang Technological University, Singapore
awkng@ntu.edu.sg
Kasun De Zoysa
University of Colombo, Sri Lanka
kasun@ucsc.cmb.ac.lk