Are You Stealing My Data? And Other Questions You Should Ask Your AI Provider

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At zeb, we prioritize AI security, governance, and performance. Here’s what you should consider when choosing an AI provider—and how we ensure you get the right answers.

The critical importance of AI privacy and security

AI systems process vast amounts of data, including sensitive company information. Security is nonnegotiable. Without strict security protocols, AI providers may retain user data indefinitely, use it for model training without consent, or expose it to breaches. Before committing to an AI partner, businesses must scrutinize data protection measures, including:

• Encryption Standards – Does the provider use enterprise-grade encryption for data in transit and at rest?
• Access Controls – Are there fine-grained access restrictions to prevent unauthorized use?
• Security Audits – How often are they conducted, and how are vulnerabilities identified, reported, and remediated?
• Privacy Impact Assessments – How frequently are PIAs conducted, and how does the provider ensure compliance with evolving privacy regulations and industry standards?
• Compliance with Regulations – Does the provider guarantee adherence to GDPR, HIPAA, CCPA, and other regulatory standards?

zeb ensures your data remains secure at every stage. We implement fine-grained access controls with Unity Catalog and Mosaic AI Gateway, continuous security audit with Lakehouse Monitoring, and clear data retention policies, giving you full control over your information. Our commitment to achieving the highest levels of data security and compliance is unwavering.

Ensuring AI accuracy with Retrieval-Augmented Generation (RAG)

AI models can become outdated if they rely solely on static training data. Retrieval-Augmented Generation (RAG) enhances AI by integrating real-time, relevant information from external sources and internal company data. This approach strengthens AI reliability by:

• Reducing hallucinations – AI responses remain grounded in verifiable knowledge, minimizing misinformation.
• Enhancing accuracy – RAG pulls in real-time, domain-specific insights, keeping AI up to date without constant retraining.
• Building a private, reliable knowledge base – By structuring and curating trusted data sources, RAG ensures AI models provide consistent and fact-based answers.

zeb’s AI solutions use RAG to ensure responses are accurate, context-aware, and seamlessly integrated with your company’s knowledge base – no constant retraining required. Our models are updated continuously to ensure they remain relevant and effective by combining it with Unity Catalog for complete data governance.

zeb’s AI solutions use RAG to ensure responses are accurate, context-aware and seamlessly integrated with your company’s knowledge base – no constant restraining required. Our models are updated continuously to ensure they remain relevant and effective.

Addressing AI bias and model drift

Bias and model drift are critical risks that can compromise AI reliability. Bias can arise from skewed training data, while model drift occurs when AI performance degrades due to evolving real-world conditions. If left unchecked, these issues can lead to unfair decision-making, reputational damage, and compliance violations. Businesses must assess how AI providers actively mitigate these risks by:

• Implementing bias detection tools – Does the AI provider use automated tools to identify and correct bias in training data and AI responses?
• Continuous model monitoring – Are AI models regularly evaluated to detect signs of drift and shifts in data patterns that could reduce accuracy?
• Retraining with unbiased data – Do they perform periodic retraining using diverse and representative datasets to maintain fairness and relevance with the AI systems?

At zeb, we take a proactive stance against bias and drift. Through our Databricks implementations, we leverage Lakehouse Monitoring to track real-time data patterns, automatically flag potential biases, and retrain models before performance deteriorates. By maintaining continuous oversight, we ensure AI solutions remain transparent, equitable, and aligned with evolving data landscapes.

Managing data retention and compliance

Data transparency is crucial when working with AI providers. Many providers retain data indefinitely, often without clear policies on deletion or customer control. Businesses should ask:

• Can I define data retention timelines?
• Is my data securely deleted when no longer needed?
• Does the provider enable full compliance with evolving regulations?

zeb puts you in control. We help clients establish retention policies, ensure secure data deletion, and maintain compliance with privacy laws.

Navigating AI compliance challenges

Regulatory landscapes are evolving, and AI providers must stay ahead of compliance requirements. Businesses should evaluate:

• How the provider tracks and maintains compliance.
• Whether they offer tools for managing sensitive data and audit trails.
• Their ability to ensure ongoing adherence to GDPR, HIPAA, CCPA, and emerging AI regulations.

zeb simplifies compliance through Unity Catalog, part of our Databricks implementations. It enables granular access controls, full data lineage tracking, and comprehensive audit trails, ensuring that companies don’t just meet regulatory standards—they stay ahead of them.

Why asking the right questions matters

Not all AI providers take security, governance, and compliance as seriously as they should. Asking the right questions helps businesses avoid costly risks, ensure AI accuracy, and maintain control over their data.

At zeb, we believe AI should be secure, ethical, and aligned with your organization’s needs. From robust security measures to real-time monitoring and compliance assurance, we provide AI solutions that businesses can trust.

Ready to work with an AI provider that gets it right? Good question. Ask some more.