In the past few years, the democratization of speech recognition and large language models has created new opportunities for voice-first platforms to automate critical workflows. Customer support is one of the most promising and vibrant areas for these innovations.
Selectra, a leading utility comparison and sales company, operates an extensive in-house fleet of on-call sales representatives and is actively embracing the new paradigm to improve agent productivity and customer experience. The company uses Gladia AI's speech-to-text engine to improve quality monitoring and extract in-depth insights from every call, continuously refining its customer experience. Here comes their story.
Selectra was founded in 2007 in France with the aim of helping consumers choose among the many electricity providers emerging on the market.
Since then, the company pursued rapid growth, reaching more than 200 million unique visitors a year to its websites. Now active in 17 countries, it has expanded across verticals – insurance, telecom, banking and others – and now caters to both individual consumers and companies through educational content and dedicated call center support.
The company receives thousands of inbound calls daily from customers who want to learn more about the different providers. During the call, the call agent’s goal is to suggest the best offer for the customer. In France alone, the company has over 200 sales agents processing calls daily.
In this context, quality monitoring is key to consistently improving customer experience. The company’s dedicated quality assurance team is responsible for reviewing the quality of the call based on pre-set criteria.
Historically, the team would process the calls one by one, which involved downloading the call and reviewing each transcript in search of specific words and phrases to ensure compliance with internal protocols.
The process was time-consuming, but with the emergence of Large Language Models (LLMs), Selectra could automate it in part by feeding the call transcripts to the model and letting the latter determine the degree of compliance and extract necessary insights.
This substantially accelerates the work of the human agents, as all they need to do in this case is validate the model’s findings using Selectra’s internal platform, built specifically for the new workflow.
In parallel, the company began to leverage speech-to-text technology to acquire more in-depth insight into customer needs and sentiments and analyze sales reps’ performance in more detail.
To make all of the above possible, Selectra looked for a speech-to-text API to provide a solid foundation for the internal quality assurance and analytics platform, combining the following:
Enter Gladia! With Gladia, Selectra was able to implement the following product features and improvements:
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After deciding to add audio transcription to the new quality monitoring project, Selectra started testing the API immediately. By working with the Gladia team to iterate and scale up, they saw a noticeable impact on the efficiency of the quality assurance workflow:
Today, the Selectra team is already considering how they can leverage Gladia’s transcription further with the audio intelligence add-ons (like chapterization, NER and others), as well as our product's real-time capabilities.
As speech recognition and LLMs become more advanced, Selectra is convinced that metadata from calls will be used in multiple new ways moving forward, enabling them to extract truly granular insights from every customer interaction. We thank Selectra for their trust and looking forward to pushing the boundaries of what speech recognition together.
Gladia provides a speech-to-text and audio intelligence API for building virtual meeting and note-taking apps, call center platforms, and media products, providing transcription, translation, and insights powered by best-in-class ASR, LLMs and GenAI models.
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Speech-To-Text
Over the last few years, Large Language Models (LLMs) have become accessible and transformative tools, powering everything from customer support and content generation to complex, industry-specific applications in healthcare, education, and finance.
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Speech-To-Text
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