Make an impact by leveraging your text data.
Let your insights inform future decisions with accuracy and impact, through Kepler’s superior Natural Language Understanding approaches.
When it comes to leveraging your text data, efficiency is vital. Kepler gets you there, no ML experience required.
Unstructured, long-form text is a prevalent but underused asset within many enterprises. Text data can come in the form of emails, online reviews, library archives, and more. Unlike tabular data, information embedded in text is free-form, so manually extracting meaning can be a highly inefficient process. Kepler’s powerful Automated Data Science Workflows accelerate the most common use cases for text data with the following objectives in mind: generating revenue, cutting costs or gaining insights. Examples include sentiment analysis of product reviews and customer processing of email inquiries.
Harness your text data with the following Automated Data Science Workflows:
Clustering makes sense of your unlabelled data by grouping them into categories according to patterns and similarities. Employ it for customer segmentation or personalizing content according to relevance and preference.
Classify key information and predict their categories to drive efficiency. Classification is optimal for automating back-office paperwork, conducting sentiment analysis of emails and reviews, and reducing turnover.
Identify and tease out irregularities in your dataset. Use Anomaly Detection to detect fraud, analyse probable causes in supply chain operations, and predictive maintenance of manufacturing equipment.
Automated Data Science Workflows with Kepler
Be at the forefront of AI-driven enterprises. Benefit from AI with a platform that requires zero Machine Learning experience and offers state-of-the-art, easy-to-use automated workflows for a seamless user experience.
Learn, onboard and implement faster than the competition with a partner that will shepherd you on your innovation journey, from start to scale.