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How This Startup Is Implementing NLP Technologies To Better Understand Customer Voice

How This Startup Is Implementing NLP Technologies To Better Understand Customer Voice

Ambika Choudhury

With the advancements in natural language processing, speech recognition, and deep learning, at the present era, support teams have started using Voice AI more efficiently and intuitively than ever by putting the data to practical use. With more voice data, support teams will better understand performance trends and make predictions. New integrations and alliances will also help teams leverage learnings from Voice AI across other channels, including email and chat. 

With a passion for transforming contact centres by turning every agent into the best brand representative, California-based Observe.ai is leveraging the latest speech and natural language processing technologies to enable organisations quickly analyse voice calls with 100 per cent accuracy. Recently, the company raised an additional 26M from top-tier investors in the U.S. and India. Currently, the company has offices in San Francisco and India and are planning to open a new office in Dallas.

Founded by Swapnil Jain, Sharath Keshavanarayana and Akash Singh in 2017, Observe.ai is an AI-powered agent enablement platform for voice customer service. With the help of Observe.ai, support teams improve call quality, monitor compliance, and coach agents.



Flagship Product

Observe.ai is a voice AI platform that transcribes and analyses voice customer service calls by using the latest speech recognition, natural language processing, and deep learning technologies. Once calls are transcribed, the transcription, along with audio analysis and metadata are processed through deep learning in which keywords, sentiment analysis, silence and pause analysis, and metrics are extracted. The result is a comprehensive reporting on contact centre and individual agent performance, which include emotion, dead-air, empathy, redaction, AHT, and supervisor escalation and others.

Use of AI and ML

Observe.ai uses machine learning and analytics for coaching people and improve their support conversations to drive operational efficiencies in contact centres. The main technologies in the voice AI product are automatic speech recognition (ASR), natural language processing (NLP), and universal language models.


W3Schools

According to the founders, they have created a solution to issues related to low-quality audio, varying accents and vocabulary by providing a feature that enables users to add custom contact centre vocabulary so that the ASR system can boost the recognition of these words. Moreover, the generic ASR models are being fine-tuned with the customer-specific data. In order to improve the overall performance for tasks like identifying the speech and sentiment of calls, ASR and NLP techniques are separately worked upon, and models are fine-tuned to meet the unique needs of contact centres.

Hiring Talents

To this question, the founders said, “we are hiring for roles across every department in our Bengaluru, San Francisco, and future Dallas office.” The office in Bangalore is in Koramangala and the current job positions opened are machine learning engineer, backend engineer, frontend engineer, marketing designer, product manager, among others.

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Click here to apply for the jobs.

Potential Competitors

Talking about potential competitors, speech analytics companies including Callminer, Contact Lens from Amazon Connect, VoiceOps, and NICE Nexidia are being considered by the founders.

Roadmap

The mission of Obeserve.ai is to transform the 300B voice customer service industry by turning every agent into your best brand representative through AI-based insights and coaching. According to the founders, in the next five years, the company will continue to improve the quality automation, improve reporting across an entire organisation down to the individual agent and understand performance better across the organisation by applying new ways to analyse and visualise performance.

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