Customer interactions on communication channels like social media, SMS messaging, and chatbots generate large amounts of conversational text. This unstructured data contains valuable information about product or service issues, sentiment, feedback, and more but it may also contain personally identifiable information that is subject to regulatory control. Therefore, access to this conversational text for analysis is often limited or completely restricted in its raw form.
You can integrate the Data Privacy for Chat service into your existing data pipelines like Databricks, NiFi, Kafka, and many more. Kubernetes deployment of the NLP model allows you to scale demanding text classification workloads. By deploying the model to CUDA accelerated hardware you can support real-time de-identification.
Contact us to learn how Privitar Data Privacy For Chat can help you responsibly analyze conversational chat text while protecting sensitive data.