Rain Raises $11M to Create Voice Experiences for Brands – Natural Self Esteem

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The shift to working from home during the pandemic has transformed workers’ technology habits, including – as the data suggests – in relation to voice assistants. For example, according to a 2020 report by Voicebot.ai and Cerence, more people are using voice assistants in cars than on smart speakers.

As usage increases, brands are expressing increasing interest in engaging with customers through voice. Even before the pandemic, companies were optimistic about language technologies. A 2018 Pindrop survey found that 84% of companies expect to use voice technology with their customers in 2019. And in 2019, 76% of companies using voice and chat assistants reported “quantifiable benefits,” according to Capgemini, with over 58% saying gains from activities like e-commerce via voice exceeded their initial expectations have surpassed.

A growing number of high-profile vendors are occupying a speech recognition market predicted to be worth $22 billion by 2026, but one of the lesser-known startups on the scene, Rain Technology, claims to be more successful than most. Based in New York, Rain works with companies and brands such as Nike, Amazon, Starbucks, Dreamworks and Unilever to create “speech experiences”, including for the car and smart speakers.

Building voice experiences for brands

Rain, a technology and design agency, helps clients conceptualize, build, and manage voice experiences that integrate with brand services and ecosystems. The experiences can come in the form of bespoke voice assistants or third-party apps on top of existing assistants like Alexa, Google Assistant and Siri. Rain’s assistant experiences are accessible on smart devices, PCs, products and custom hardware, the company says, and they give organizations “full control” over their behavior and unlimited access to data and analytics.

“Rain was originally founded by Brian Edelman and Nick Godfrey. [I] was hired as CEO in 2016 as the company shifted its focus to voice and conversational AI,” CEO Nithya Thadani told VentureBeat via email. “When Rain got started with voice technology, there were many early signs that voice as an interface would become ubiquitous as smart speakers took off at an incredible rate, even faster than the smartphone.”

Rain says it has spoken for over 20 Fortune 500 companies and created more than 70 experiences with 15 million monthly interactions. For example, Rain built an Alexa app for Starbucks that allows Starbucks customers to place pickup orders by saying a command like “Alexa, ask Starbucks to start my usual order.” For Headspace, Rain launched a guided meditation voice app for Microsoft’s Alexa, Google Assistant, and Cortana.

One of Rain’s voice experiences, built for the Google Assistant.

Beyond consumer-centric apps, Rain works with companies to create voice-enabled tools for workers across a range of industries, including construction. Among other things, the company claims to have developed a voice assistant for a construction company to track construction project details and a voice-enabled in-store experience for a “global luxury retailer”.

“Through our work in Voice, we saw an opportunity to develop people-centric voice solutions for the deskless worker – skilled workers in industries such as agriculture, healthcare, construction and manufacturing. Despite making up 80% of the global workforce, this audience has been drastically underserved by technology – a reality that has been emphasized during the pandemic,” Thadani said. “For employees, speech is a natural fit for functions like quick data entry or quick data retrieval, where simply saying a sentence can do laps around menu bars and keyboards.”

Thadani cites statistics showing that workers are willing to use language technologies in the workplace – or at least try to. In a 2019 report, Gartner predicted that 25% of digital workers will be using virtual employee assistants on a daily basis by 2021. And a recent Opus poll found that 73% of executives see the value of voice in “operational efficiency.”

“Machine learning has powerful capabilities to support the proper routing and handling of complex conversational AI requests,” said Thadani. “For example, automotive repair professionals rely on multiple data sources to inform their work — databases that are structured differently on both the front-end user interface and the back-end. Surprisingly, these sources can give different answers to the same questions, such as: B. “Tell me the oil capacity of a vehicle” or “What is the torque for a wheel nut”. Choosing which database to consult and which specification to use can be far from easy and time-consuming for engineers. We investigate how we can use machine learning to model the technician’s decision-making process so that we can provide the “best” answer to any repair question across multiple data sources, thereby saving the technician time and improving the overall quality of their repair work. ”

Next Steps

As the voice market is poised for growth — Edison Research estimated in 2019 that more than 53 million Americans alone owned a smart speaker — competing agencies, including Skilled Creative, are competing for a piece. But Thadani points to Rain’s traction to date, including an $11 million funding round led by Multiply Group’s venture arm announced today. This brings Rain’s total capital to nearly $15 million.

Rain, with its 25 employees, plans to use the funds from the latest round of funding for “growth and expansion,” primarily for hiring and product development in the automotive industry. The company recently expanded its West Coast operations and hired new executives, including a general manager in its Utah office and a vice president of strategic partnerships. Investors include Valor Capital, McLarty Diversified Holdings and Burch Creative Capital.

“There are two overarching challenges to delivering on the promise of voice-enabled tools for… the unemployed workforce. First, the underlying data must be organized into complex maps of meaning for a specific domain, known as taxonomies and ontologies, which allow natural language queries to be quickly and accurately parsed to retrieve the relevant data points and return them to the user… Second, the Speech technology needs to be built and tuned to work reliably in a real-world environment, including ambient noise in a work environment and variations in user voices,” Thadani added. “Our goal is to create a language user experience that can interpret industry-specific jargon in the same way — one that professionals actually want to interact with.”

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