The EU AI Act requires explainable AI systems.
We help enterprises achieve compliance while maintaining performance.
"Qriton helped us transform our AI systems while maintaining performance. The transparency has improved trust across our organization."
Understanding the key obstacles enterprises face with AI explainability
The EU AI Act requires transparency in high-risk AI systems. We help organizations meet these requirements while maintaining system performance and competitive advantage.
Stakeholders need to understand AI decisions to trust them. Our solutions provide clear explanations that increase confidence and adoption across your organization.
Understanding why AI makes decisions enables better optimization. Transparent systems are easier to debug, improve, and scale effectively.
Combining the best of neural networks with symbolic reasoning
Comprehensive evaluation of your existing AI systems to identify transparency gaps and compliance requirements.
Adding explainability layers to your current systems without sacrificing performance or requiring complete rebuilds.
Comprehensive testing and documentation to ensure regulatory compliance and stakeholder confidence.
Continuous monitoring and updates to maintain transparency as your AI systems evolve.
Six dimensions for evaluating AI transparency
How well does your AI distinguish between known facts, inferences, and uncertainty?
Can your system explain its decision-making process in clear, logical steps?
How well does your AI adapt to changing conditions and contexts?
Does your system maintain consistent performance over time?
Can your system identify and explain causal relationships, not just correlations?
Are your AI's outcomes fair and unbiased across different groups?
Results from our enterprise implementations
Join leading enterprises who have successfully transformed their AI systems
with our proven neural-symbolic approach.