Waveline

Get insightful text analysis with machine learning that extracts, analyzes, and stores text. Train high-quality machine learning custom models without a single line of code with AutoML. Apply natural language understanding (NLU) to apps with Natural Language API. Use entity analysis to find and label fields within a document, including emails, chat, and social media, and then sentiment analysis to understand customer opinions to find actionable product and UX insights. Natural Language with speech-to-text API extracts insights from audio. Vision API adds optical character recognition (OCR) for scanned docs. Translation API understands sentiments in multiple languages. Use custom entity extraction to identify domain-specific entities within documents, many of which don’t appear in standard language models, without having to spend time or money on manual analysis. Train your own high-quality machine learning custom models to classify, extract, and detect sentiment.

Insurance is driven to get the right rate and to manage risk. In this competitive environment, alleviating areas of manual intervention are critical to separate ourselves from peers in the industry. Large staffs are required to search through, read, organize, analyze and distribute information for underwriting and support purposes. Much of the data is text-centric and unstructured needing manual review. Scaling generally entails hiring more people or outsourcing. Complaints must be filtered and registered according to topic and level of severity. Automotive companies gather these complaints in multiple ways, including emails, comments, forms, etc. Lymba’s Underwriting and Support NLP solution streamlines the text-centric bottlenecks by transforming the data into actionable knowledge; this saves time and resources by populating an initial review.