Add multilingual Voice Search capabilities in your retail ecommerce app.
Execute end to end tasks on your app using voice.
Add multiple items to your cart from your shopping list in one go.
For eg: ”Add 2kg of Onions, Half kg Amul Ghee”
Promote deals in your app using voice. Speak out offers to your customers at the right time.
Why should hands have all the fun?
Add multiple items to cart in one go.
Great qualitative review in the most natural way.
Capture the Tier 2 and Tier 3 users by enabling them to order with voice in Indic languages
Increase top-line growth by adding new users and bottom-line by increasing revenues per customer.
Make spelling mistakes a thing of the past. The friction of using keyboard, remembering spelling, transliteration challenges
Let users discover those hidden gems...err.. features in your app. Refer your friends in banking; the horror of finding features is real in those apps.
Add Slang to your app in as few as two days.
Pay for only 'Monthly Slang users'- those customers who used Voice in your app once.
Bias our speech recognition models specifically for your app to enable very accurate recognition.
We will only pass relevant words to the app, whatever you might say
We provide dynamic hints on the Slang Surface. This helps in guiding the users about 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 user to speak before zonking out. Did we already mention that we designed Slang with empathy?
Some people speak more than others (Our CEO🤷🏽), We get that, we don’t stop listening to the user if she’s in the middle of a long sentence.
There are two ways of triggering the Voice Assistant. Global and inline search.
Ask a question to the user. Wait for her to reply and even speak out a confirmation message. Remove the hesitation in going wrong.
We support 5 Indian languages out of the box - Indian English, Hindi, Tamil, Kannada and Malayalam.
We reduce the overhead on your backend by giving the translated query from any of these 5 Indian Languages to English.
Have control over the words and phrases which you don’t want to translate. Bias our translation engine according to your app
Analyze how your users are using voice, what they are speaking most commonly, how often and much more.
Understand which words users have been spoken most often. A way to the user's mind is through her words. (Plain ol’ word cloud but...well marketing dept 🤷 )
Understand the language and regional breakdown of users.
World’s first VAaaS platform provides a suite of domain specific Voice Assistants for mobile and web apps.
Training NLP & Speech Recognition models
New vernacular languages
Infrastructure & lifecycle management
All taken care of by the platform.
Pre-trained NLP Models
Go-Live under 30 mins, not months!
Domain specific NLP and Speech recognition models deliver out-of-box high accuracy.
Every domain has its own nuances. Speech Recognition models that we use are trained specifically for each domain and dynamically improves over time.
Our NLP models are pre trained to understand the vocabulary of your app to get even higher accuracy.
Intuitive voice experiences based on years of on-field research, delivered to production in your first rollout.
Users can invoke the Voice Assistant using touch or the app can invoke it automatically.
After a voice command is completed, our voice assistant continues to listen for more queries.
On screen contextual Visual hints, guide the user to complete intended tasks using voice.
Allow users to speak long & short form natural sentences to get things done in your app.
Multilingual Voice Assistant on top of your English app.
Our voice assistant supports 5 Indian languages - English, Hindi, Tamil, Kannada and Malayalam.
The user's inputs are converted to English irrespective of what language they speak so that your app can continue to be in English.
Bias our translation engine to have control over the words and phrases which you don’t want to translate.