Y Meadows is built to understand human intent from written messages, which can come in through a variety of channels like email, online chat, webforms, etc.
Our solution leverages deep learning neural net NLP models that enable the use of context (not just keywords or rule-based formats) to process and understand a message.
Since context is unique and specific to each and every business, our customers' language models are first pre-trained using their very own data.
Based on the intent determined by the NLP model, the support message (ticket or case) is processed through a predetermined sequence of workflow actions or steps, which we call a "Journey."
Journey workflows (customer service automation) can have a wide variety of use cases, ranging from simple to complex, and even resolve customer support issues fully automatically.
Examples include rerouting a message to a different department, pull information related to a particular support case from separate databases, or responding directly to a customer.
Although Y Meadows enables support teams to automate the resolution of a large variety of customer support issues, some cases require an additional layer of security and can't be automated.
The option for human review and corrections is one of our core values, which is why we've designed the "Review Panel."
As reviewers mark system decisions as correct or incorrect, the model becomes smarter and more accurate over time.