Dashbot, a conversational artificial intelligence and data platform provider, launched Conversational Data Cloud, letting companies build and optimize their chatbots from their own conversational data and turn unstructured, noisy, interrelated and often tangled conversational data into immediate action.
Dashbot’s Conversational Data Cloud enables businesses to do the following:
- Centralize all conversational data, including chatbot transcripts, Zendesk, email, and live agent voice calls;
- Decipher tens of thousands of daily conversations and transcripts; and
- Group similar messages and topics to determine areas of failure and opportunities for new use cases leveraging machine learning.
“We’re expanding beyond reporting and analytics to be able to ingest raw conversational data, which can be difficult but also very valuable for our customers,” said Andrew Hong, CEO of Dashbot, in a statement. “We’re on a mission to decipher the language, which is one of the most complex data types ever. We listened to our customers challenged to make sense of their conversational data, so we built our Conversational Data Cloud to help businesses automate, analyze, and optimize their conversation channels.”
Dashbot’s Conversational Data Cloud is powered by the following features:
- Transcript Transformer, to search and categorize thousands of daily transcripts;
- DashbotML, with machine learning models hyper tuned from more than 10 billion conversations. Topic Modeling can visualize flow and conversation loops, and Phrase clustering (message grouping) can identify new use cases and unhandled topics;
- Automated Training Data that can be exported to optimize natural language, processing models.
