The vast amounts of data used to train AI systems raise significant security and privacy concerns regarding the exposure and leakage of sensitive information. If data is not properly encrypted or anonymized, both at rest and in transit, sensitive information can be at risk of leakage.
Rogue chat users or agents can steal data or model parameters, leading to widespread data breaches or intellectual property theft, which can result in significant financial and legal harm to an enterprise.
The lack of explainability, observability, and quantifiable data metrics makes it challenging for AI teams to certify that a particular data set or model is ready for deployment in compliance with multiple regulations, including ISO 42001, the EU AI Act, and various US state laws.
When enterprises lack the ability to fully understand and control their data, they struggle to identify where sensitive data resides, leading to security gaps. It is crucial to classify data and apply governance policies to ensure compliance and address anomalies effectively.
AI algorithms can be biased, which can impact governance decisions. To address this challenge, enterprises must ensure that the data used to train these models is as unbiased and representative as possible. Failing to take these measures can lead to negative consequences and cause harm.
By maintaining a comprehensive inventory of AI models with associated risk profiles, Secuvy ensures that your organization meets compliance requirements with ease.
Automated scrubbing of PII and sensitive data ensures compliance with global data protection regulations, EU AI Act, ISO 42001, and US State laws reducing the risk of fines and legal complications.
Secuvy uses contextual data classification to block LLM responses and RAG data in real-time, effectively preventing data leakages. Our AI’s data association and linkage capabilities uniquely thwart attacks aimed at extracting sensitive information and IP identifiers.
The ability to delink user identities across data sources protects individual privacy and minimizes the risk of data breaches.
Define and enforce policies that reduce bias and promote fairness, ensuring ethical AI practices that build trust with stakeholders.
Save time and resources by leveraging AI to automatically discover, classify, and manage sensitive data, reducing the manual workload for your teams.
Optimize your training datasets to decrease storage costs, accelerate training times, and improve the overall quality of AI models, leading to better business outcomes.
Monitor and improve the fairness and bias of AI models with QoS metrics, ensuring that your AI systems produce equitable outcomes and maintain ethical standards.
By minimizing and cleansing training data, Secuvy enhances model accuracy and efficiency, leading to more reliable and effective AI solutions.