With workplaces and product deliveries increasingly moving to smartphones, learning is also becoming mobile. As per research, English fluency improves professional income by 34%. With over 200 million white and blue-collar workers and job seekers in the economy, English learning has become an important part of workplace skills requirements by employers.
With such a vision, Pune-based startup, Utter uses conversational chats (chatbots and private tutors) as a medium to improve the functional fluency of job seekers. Founded by Ninad Vengurlekar and Amit Bhadbhade in 2015, Utter combines seamless interactions between machines and humans to achieve low cost affordable English practice to learners.
Ninad is a Masters in Edu Technology from Harvard Graduate School of Education while Amit is a Masters in Mobile Programming from Lancaster University, UK. Utter uses conversational chatbots combining with live chats to improve the English fluency of aspiring white-collar and blue-collar workers.
The Utter App was launched in January 2018 on Google Play and currently has over 2.5 million users across India, Bangladesh, Myanmar, and Kuwait. It is a paid app which is priced between ₹199 to ₹499 with over 60,000 paid users. Utter has raised around $1.3 million through Unitus Ventures and a clutch of angel investors and is currently doing an ARR of over ₹3 crores a year on an MAU base of 450,000.
Utter’s flagship product is an English learning app that was born out of the features the founders integrated while observing the WhatsApp Group interactions. Utter was build by transforming chat bubbles into byte-size learning tools with features like translations, dictionary, and text to speech in order to radically improve fluency. The app also has an option to practice fluency with live tutors who undertake in chat corrections to point out language errors in complete privacy. The platform offers them an unlimited bank of conversations in multiple scenarios of their personal and professional life.
Use of AI/ML and Other Techniques
Utter uses the live and automated chat interactions to build conversational patterns of each user. A part of these patterns is used to create personalised learning experiences. The conversational patterns in live chats are used to build automated suggestions to tutors so that they can speed up their responses to learners. Utter also aspires to build automated voice bots through the millions of conversational data interactions it would be automating.
According to the founders, byte-sized conversations are the future of learning. Utter is poised to build low-cost affordable learning solutions at scale for the millions of emerging jobs in the internet economy. Currently, the users in the internet economy learn the most through their smartphones and by collecting competency maps of byte size learning conversations and later automating them through ML and AI, one can afford low-cost learning solutions.
Tackling The Hiring Phase
Coming to the hiring phase, the founders said, “Utter is a small team of 14 people and what we look for in our candidates is the integrity of purpose to build something transformative and world-changing. So apart from technical skills, what we look for is the initiative and passion that they bring to the table. The latter is more valued than the former. Because the former can be learned and fine-tuned, the latter is a part of a candidate’s DNA.”
Talking about competitors, companies like Open English, iTutorGroup, and VIPKid are considered as potential competitors.
For the future roadmap, Utter aspires to move beyond chat as the only mode of learning in the future. The founders aspire to take conversational learning to audio and video platforms like Voice Assistants, internet TV, and Online Radio.
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A Technical Journalist who loves writing about Machine Learning and Artificial Intelligence. A lover of music, writing and learning something out of the box.