Just connect conversational AI supports in 92% cases

The advanced chatbot can now provide end-to-end robotic support in 92% of cases conversational AI supports in 92% of cases., the world’s leading customer support automation platform, has been a pioneer in automating customer support with its deep and insightful machine learning patterns formed across languages and dialects since 2015. This startup, which now supports over 15,000 companies in over ten languages such as English, Hindi, Arabic, Konkani, Tamil, Telugu, Kannada, Hinglish, and more, has developed its product on Google Cloud.

In a detailed case study on Google Cloud, Gaurav Singh, the CEO & Founder of, elucidates how the platform helped them concentrate on core resources allowing time and mind space for achievable innovations.

“Google Kubernetes Engine, Google AI, and data storage tools give us the scaling power, low-latency, and creative freedom to turn our vision into reality,” said Gaurav Singh.’s chatbot devised a solution specific to a few key industries in a one-size-fits-all world: e-commerce, banking, real estate, and a deep insight into the end-to-end journey of these sectors. The advanced chatbot can now provide end-to-end robotic support in 92% of cases without human intervention.

The Google case study finds also depends on Cloud Logging and Cloud Monitoring to offer 24/7 customer support even while running major system upgrades and unexpected demand spikes. The startup once saw peak loads of six to ten times its usual load over two quarters, but Google Cloud had seamlessly accommodated the excess traffic, without the team having to worry about it.

Added to that, being a part of the cloud infrastructure helps’s engineers solve problems as they happen. “An integrated logging, monitoring, and alerting system allow our engineers to trade issues across the microservice landscape and identify and resolve problems quickly,” said Singh. innovated an Oracle-like chatbot that can speak multiple languages; it uses various Google technologies and its natural language processing stack (NLP), including TensorFlow. “More than 80% of our natural language queries are answered using transformer-based models, a key contribution from Google Research,” said Singh.

The full article on the Google Cloud case study is available​ here:

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