Compare the Top AI Governance Tools that integrate with SQL Server as of July 2025

This a list of AI Governance tools that integrate with SQL Server. Use the filters on the left to add additional filters for products that have integrations with SQL Server. View the products that work with SQL Server in the table below.

What are AI Governance Tools for SQL Server?

AI governance tools are software tools designed to help companies and organizations manage the ethical and responsible use of artificial intelligence. These tools provide a framework for developing and implementing policies, procedures, and guidelines related to AI. They also offer monitoring and reporting features to ensure compliance with these regulations. With the rise of AI technology, these governance tools play a crucial role in promoting transparency and accountability in decision-making processes involving AI. Additionally, they aim to strike a balance between innovation and ethical considerations by providing guidance on issues such as bias, privacy, and security. Compare and read user reviews of the best AI Governance tools for SQL Server currently available using the table below. This list is updated regularly.

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    DataHub

    DataHub

    DataHub

    DataHub is an open source metadata platform designed to streamline data discovery, observability, and governance across diverse data ecosystems. It enables organizations to effortlessly discover trustworthy data, with experiences tailored for each person and eliminates breaking changes with detailed cross-platform and column-level lineage. DataHub builds confidence in your data by providing a comprehensive view of business, operational, and technical context, all in one place. The platform offers automated data quality checks and AI-driven anomaly detection, notifying teams when issues arise and centralizing incident tracking. With detailed lineage, documentation, and ownership information, DataHub facilitates swift issue resolution. It also automates governance programs by classifying assets as they evolve, minimizing manual work through GenAI documentation, AI-driven classification, and smart propagation. DataHub's extensible architecture supports over 70 native integrations.
    Starting Price: Free
  • 2
    ModelOp

    ModelOp

    ModelOp

    ModelOp is the leading AI governance software that helps enterprises safeguard all AI initiatives, including generative AI, Large Language Models (LLMs), in-house, third-party vendors, embedded systems, etc., without stifling innovation. Corporate boards and C‑suites are demanding the rapid adoption of generative AI but face financial, regulatory, security, privacy, ethical, and brand risks. Global, federal, state, and local-level governments are moving quickly to implement AI regulations and oversight, forcing enterprises to urgently prepare for and comply with rules designed to prevent AI from going wrong. Connect with AI Governance experts to stay informed about market trends, regulations, news, research, opinions, and insights to help you balance the risks and rewards of enterprise AI. ModelOp Center keeps organizations safe and gives peace of mind to all stakeholders. Streamline reporting, monitoring, and compliance adherence across the enterprise.
  • 3
    OneTrust Data & AI Governance
    OneTrust's Data & AI Governance solution is an integrated platform designed to establish data and AI policies by consolidating insights from data, metadata, models, and risk assessments, providing comprehensive visibility into data products and AI development. It accelerates data-driven innovation by increasing the speed of approval for data products and AI systems. The solution enhances business continuity through continuous monitoring of data and AI systems, ensuring regulatory compliance, effective risk management, and reduced application downtime. It simplifies compliance by centrally defining, orchestrating, and natively enforcing data policies. Key features include consistent scanning, classification, and tagging of sensitive data to ensure the reliable application of data governance policies across structured and unstructured sources. It promotes responsible data usage by enforcing role-based access within a robust data governance framework.
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