Data-centric ML tools

    Aquarium helps teams streamline the process of finding issues, validating fixes, and adding data for their machine learning datasets.
    Trusted by the best ML teams

      Improve data quality

      • Bad data harms model performance. Easily find and fix data quality issues in a visual interface.
      • Make sure you're training and testing your model on clean data.
      Learn how to better understand your data

      Analyze model errors

      • Find the most critical patterns of failures in your data and model performance.

        Always prioritize the work that will improve your model the most.
      Run faster failure analysis

      Target your data collection

      Many problems in machine learning can be solved with collecting more data, but not all data is equal.
      Collect data that gets you the most model improvement for the least labeling spend.
      Learn how to collect meaningful data

        Integrate into your ML stack

        • Integrate Aquarium into your existing ML stack with an intuitive Python Client API.
        • Set up automated workflows around your ML data operations.
        Integrate with Aquarium easily

        Operationalize ML

        • Empower your data operations team to constantly find and fix problems with your dataset.
        As your datasets get better, your models get better.
        Learn how Aquarium improves workflows

        Supported Data Types

        Aquarium For Enterprise

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        Scalability and reliability

        The more data you have, the more value we offer. Aquarium reliably scales to datasets containing tens of millions of datapoints.

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        Data security

        Aquarium is SOC2 Type 2 certified. We also offer Anonymous Mode for organizations who want to use Aquarium without exposing any sensitive data.

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        Hands-on support

        Aquarium offers solutions engineering resources, customer success syncs, and user training to help customers get to value.

        Get in touch

        Schedule time to get started with Aquarium