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что приготовить ребенку на 5 лет на день рождения, The Top 10 AI Compliance Tools of 2025 - Centraleyes, Benchmark Best 25 AI Governance Tools in 2025 - AIMultiple, Top 12 AI Governance Tools in 2025 - aimojo.io, AI Compliance tool - PwC, AI risk and approaches to global regulatory compliance, Regulatory & Corporate Compliance Enterprise Software - Archer IRM, AI for regulatory compliance: Use cases, technologies, benefits .
Figure 4: Monitaur platform, an example AI governance tool 3 Sigma Red AIDetects and mitigates biases, ensuring model explainability and facilitating ethical AI practices.Solas AIChecks for algorithmic discrimination to increase regulator and legal compliance.Top data governance platformsData governance platforms contain various tools and toolkits primarily focused on data management to ensure the quality, privacy and compliance of data used in AI applications. They contribute to maintaining data integrity, security, and ethical use, which are crucial for responsible AI practices.Some of these platforms can help check compliance and overall AI lifecycle management. These platforms can be valuable for organizations implementing comprehensive AI governance frameworks. Here are a few examples:ClouderaA hybrid data platform that aims to improve the quality of data sets and ML models, focusing on data governance.DatabricksCombines data lakes and data warehouses in a platform that can also govern their structured and unstructured data, machine learning models, notebooks, dashboards and files on any cloud or platform.Devron AIOffers a data science platform to build and train AI models and ensure that models meet governance policies and compliance requirements, including GDPR, CCPA and EU AI Act.IBM Cloud Pak for Data IBM’s comprehensive data and AI platform, offering end-to-end governance capabilities for AI projects:Figure 5: IBM Openscale, an example from a data governance tool 4 SnowflakeDelivers a data cloud platform that can manage risk and improve operational efficiency through data management and security.Top MLOps platformsLeading MLOps platforms provide tools and infrastructure to support end-to-end machine learning workflows, including model management and oversight.Amazon SagemakerAmazon SageMaker is a managed AWS service that enables users to develop, train, and deploy machine learning models at scale. It simplifies the process of building, training, and deploying machine learning models, considering AI governance practices.Figure 6: Amazon Sagemaker ML governance dashboard, an MLOps platform 5 DatarobotDelivers a single platform to deploy, monitor, manage, and govern all your models in production, including features like trusted AI and ML governance to provide an end-to-end AI lifecycle governance.Vertex AIOffers a range of tools and services for building, training, and deploying machine learning models with AI governance techniques, such as model monitoring, fairness, and explainability features.Compare more MLOPs platforms in our data-driven and comprehensive vendor list.Top MLOps toolsMLOps tools are individual software tools that serve specific purposes within the entire machine learning process. For example, MLOps tools can focus on ML model development, monitoring or model deployment. A data science team can deliver responsible AI products by applying these tools to machine learning algorithms to:, The Government’s Embrace of AI Risk and Compliance Tools. The potential of artificial intelligence (AI) to revolutionize business operations has garnered significant attention. However, what often goes unnoticed is the U.S. government’s rapid adoption of AI and sophisticated data analytics to uncover corporate wrongdoing. Federal agencies, from the Securities and Exchange Commission (SEC , Delivers AI model risk management, model governance and compliance assessments with an emphasis on generative AI to facilitate the adoption of AI technology. Credo AI delivers: Credo AI delivers: Regulatory compliance to streamline adherence to regulations and enterprise policies, including preparations for new laws like the EU AI Act..
Monitaur ML Assurance is a leading AI governance platform designed to help organizations build and deploy responsible AI systems. Founded in 2019 by a team of experts in corporate innovation, machine learning, and software development, Monitaur offers a comprehensive suite of tools for AI risk management and compliance.. The platform's unique “policy-to-proof” approach enables businesses , PwC Czech Republic offers an AI Compliance Tool to help guide you navigate the complex regulatory AI landscape in response to the EU’s AI Act. The tool would guide your technical, business and risk and compliance teams through the requirements of the AI Act and provide them with a single platform to cooperate and document the compliance of separate AI projects within your organisation., It identifies the patterns, trends, and strategic implications in an evolving regulatory landscape to support companies with their compliance journeys. AI is arguably already one of the most important strategic priorities for businesses. However, alongside the potential opportunities, there are widespread concerns about AI’s risks. In , Archer AI Governance is designed to help risk managers ensure the responsible use of AI across the organization. Aligned with the EU (European Union) AI Act, the use case provides risk managers with tools and capabilities to manage AI risks, maintain compliance, and promote ethical AI practices., Discover the transformative power of AI for regulatory compliance, optimizing compliance processes, ensuring legal adherence, and enhancing risk management. The Hackett Group Announces Strategic Acquisition of Leading Gen AI Development Firm LeewayHertz. Read more. Toggle Toggle. AI PRODUCTS. Enterprise GenAI Platform. AI Copilot for Sales. AI Research Solution for Due Diligence. GenAI , Overall, AI can be a valuable tool for compliance officers; it can help them to identify potential risks, monitor employee behavior, generate reports, provide recommendations, and educate employees about compliance. But compliance officers will need to carefully navigate the interplay between these powerful tools, the data that they are applied to, and the results and recommendations that are .