Question: I need a solution to categorize large amounts of text data into industry-standard categories, can you help?

Taylor

For classifying large swaths of text data into industry-standard categories, Taylor stands out. It can use taxonomies like NAICS, O*NET SOC and IAB to classify and label text data. With high accuracy (99.9%+), fast classification and easy integration through API or spreadsheet tools, Taylor is well suited for automating data classification and standardizing unstructured text. With flexible pricing tiers for individuals, small teams and large enterprises, Taylor can be adapted to suit your needs.

NuMind

Another good option is NuMind, a machine learning platform that lets you build text processing models without writing any code. NuMind can classify multilingual text and perform other tasks like sentiment analysis, entity recognition and content moderation. Its models are designed to be efficient and economical, making it good for tasks like data entry and routing customer service calls. NuMind's pricing tiers range from educational projects to heavy enterprise use.

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