Question: Is there a platform that can help me categorize and label large volumes of text data from support tickets?

If you need a platform to categorize and label lots of text data from support tickets, Metatext could be a good option. It lets you train your own NLP models using large language models, which can automate text classification and tagging. It's well suited for customer support, with tools to categorize and extract useful information from tickets, and to help you manage and analyze your customer interactions.

Another option is Taylor, a text classification API that uses industry-standard taxonomies to categorize and label text data without requiring a lot of infrastructure or maintenance. It's got high accuracy, fast classification and an easy integration by API or spreadsheet, so it's good for standardizing and analyzing unstructured text data from support tickets.

If you want a no-code option, MonkeyLearn offers a text analytics tool that can clean, label and visualize customer feedback. It comes with pre-trained and custom machine learning models for text classification and integrates with popular apps like Zendesk and Freshdesk so you can automate text analysis and get immediate insights.

Last, Forethought is an AI-powered customer support platform that automates routine work, improves resolution rates and lowers support costs. It's got tools like Triage for assessing intent and routing tickets, and Assist for generating AI-powered ticket summaries. It integrates with leading helpdesks like Zendesk and Salesforce, so it's a good option if you want to improve customer support efficiency.