Best AI Governance Tools for Amazon SageMaker

Find and compare the best AI Governance tools for Amazon SageMaker in 2024

Use the comparison tool below to compare the top AI Governance tools for Amazon SageMaker on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Dataiku DSS Reviews
    Data analysts, engineers, scientists, and other scientists can be brought together. Automate self-service analytics and machine learning operations. Get results today, build for tomorrow. Dataiku DSS is a collaborative data science platform that allows data scientists, engineers, and data analysts to create, prototype, build, then deliver their data products more efficiently. Use notebooks (Python, R, Spark, Scala, Hive, etc.) You can also use a drag-and-drop visual interface or Python, R, Spark, Scala, Hive notebooks at every step of the predictive dataflow prototyping procedure - from wrangling to analysis and modeling. Visually profile the data at each stage of the analysis. Interactively explore your data and chart it using 25+ built in charts. Use 80+ built-in functions to prepare, enrich, blend, clean, and clean your data. Make use of Machine Learning technologies such as Scikit-Learn (MLlib), TensorFlow and Keras. In a visual UI. You can build and optimize models in Python or R, and integrate any external library of ML through code APIs.
  • 2
    Superwise Reviews

    Superwise

    Superwise

    Free
    You can now build what took years. Simple, customizable, scalable, secure, ML monitoring. Everything you need to deploy and maintain ML in production. Superwise integrates with any ML stack, and can connect to any number of communication tools. Want to go further? Superwise is API-first. All of our APIs allow you to access everything, and we mean everything. All this from the comfort of your cloud. You have complete control over ML monitoring. You can set up metrics and policies using our SDK and APIs. Or, you can simply choose a template to monitor and adjust the sensitivity, conditions and alert channels. Get Superwise or contact us for more information. Superwise's ML monitoring policy templates allow you to quickly create alerts. You can choose from dozens pre-built monitors, ranging from data drift and equal opportunity, or you can customize policies to include your domain expertise.
  • 3
    Aporia Reviews
    Our easy-to-use monitor builder allows you to create customized monitors for your machinelearning models. Get alerts for issues such as concept drift, model performance degradation and bias. Aporia can seamlessly integrate with any ML infrastructure. It doesn't matter if it's a FastAPI server built on top of Kubernetes or an open-source deployment tool such as MLFlow, or a machine-learning platform like AWS Sagemaker. Zoom in on specific data segments to track the model's behavior. Unexpected biases, underperformance, drifting characteristics, and data integrity issues can be identified. You need the right tools to quickly identify the root cause of problems in your ML models. Our investigation toolbox allows you to go deeper than model monitoring and take a deep look at model performance, data segments or distribution.
  • 4
    Fiddler Reviews
    Fiddler is a pioneer in enterprise Model Performance Management. Data Science, MLOps, and LOB teams use Fiddler to monitor, explain, analyze, and improve their models and build trust into AI. The unified environment provides a common language, centralized controls, and actionable insights to operationalize ML/AI with trust. It addresses the unique challenges of building in-house stable and secure MLOps systems at scale. Unlike observability solutions, Fiddler seamlessly integrates deep XAI and analytics to help you grow into advanced capabilities over time and build a framework for responsible AI practices. Fortune 500 organizations use Fiddler across training and production models to accelerate AI time-to-value and scale and increase revenue.
  • 5
    WhyLabs Reviews
    Observability allows you to detect data issues and ML problems faster, to deliver continuous improvements and to avoid costly incidents. Start with reliable data. Monitor data in motion for quality issues. Pinpoint data and models drift. Identify the training-serving skew, and proactively retrain. Monitor key performance metrics continuously to detect model accuracy degradation. Identify and prevent data leakage in generative AI applications. Protect your generative AI apps from malicious actions. Improve AI applications by using user feedback, monitoring and cross-team collaboration. Integrate in just minutes with agents that analyze raw data, without moving or replicating it. This ensures privacy and security. Use the proprietary privacy-preserving technology to integrate the WhyLabs SaaS Platform with any use case. Security approved by healthcare and banks.
  • 6
    Qlik Staige Reviews
    Use Qlik®, Staige™, to make AI real. It will provide a trusted foundation for data, automation, actionable forecasts, and a company-wide impact. AI is not just experiments and initiatives - it's a whole ecosystem of files, scripts and results. We've partnered up with the best sources to provide you with integrations that will save time, enable better management, and validate the quality of your data. Automate the delivery and management of real-time AWS data to data lakes or warehouses, and make this data easily accessible via a governed catalogue. With our new integration with Amazon Bedrock you can easily connect foundational large-language models (LLMs), including A21 Labs Amazon Titan, Anthropic Cohere and Meta. AWS customers can leverage AI-driven insights with ease using seamless integration with Amazon Bedrock.
  • 7
    ModelOp Reviews
    ModelOp is a leading AI governance tool that helps enterprises safeguard AI initiatives including generative AI and Large Language Models. It also protects in-house vendors, third-party vendors and embedded systems without stifling the innovation. Corporate boards and C suites demand the rapid adoption of generative AI, but face financial risks, regulatory, privacy, security, and ethical issues. Governments at all levels, including federal, state and local, are implementing AI regulations and overseeing the industry quickly. This forces enterprises to prepare and comply with rules that prevent AI from going awry. Connect with AI Governance specialists to stay informed on market trends, regulations and news. You can also get insights and opinions from experts. ModelOp Center helps organizations stay safe and provides peace of mind for all stakeholders. Streamline reporting and compliance across the enterprise.
  • Previous
  • You're on page 1
  • Next