We understand each domain has its own nuances. The Assistants support predefined User journeys specific to those domains.
Higher accuracy through dynamic Improvements in Speech Recognition Models by training them according to the domain.
Out of box Conversation Design designed for each user journey for each domain.
Our NLP models are pre-trained based on the SKUs and the nuances for each domain.
We support 2 Indian languages out of the box - English and Hindi, with optional support of Tamil, Kannada and Malayalam.
Have control over the words and phrases which you don’t want to translate. Bias our translation engine according to your app. Control what gets translated and how with customizable translation hints.
We reduce the overhead on your backend by giving the translated query from Indian Language to English.
Let your customer speak as they will, Slang is optimized to understand different accents.
We provide rotating hints on the Slang Surface. This helps in guiding the user of what they can speak thereby reducing cognitive overload. But Dil Maange More? We even have a hints button to show even more hints
We understand people take time to speak, so we wait for the person to speak before zonking out. Did we mention designed with empathy already?
Some people speak more than others(<emoji>Our CEO</emoji>), we won’t stop listening to the user if she is in the middle of a long sentence
A conversation is two way. The Assistant will ask questions and also talk back to your customer in the language of their choice.
Sometimes you want to talk but not the Assistant. Fear not with the mute mode option and the Assistant will only listen but never talk back
The Assistant can be invoked either via an inline trigger embedded inside the app or via a global (default) trigger that floats on top of all screens automatically