Meet the Indian Startup That’s Building a Global Entertainment Platform on the Back of AI, and How

It’s a startup born out of dissatisfaction that cracked its product-market-fit primarily through remote work. It’s one that redefined entertainment—making it a more personal and on-the-go affair—by putting it into the pockets of millions of people worldwide, starting with India, where it started its journey in 2018. Pocket FM has been revolutionizing entertainment by making audio entertainment mainstream worldwide. Founded by Rohan Nayak, Prateek Dixit, and Nishanth KS, Pocket FM is known for its flagship audio series—serialized audio dramas presented in an episodic manner—which people across the globe pay to listen to. Pocket FM isn’t just another over-the-top (OTT) entertainment player with audio at its core. The startup is known for being a disruptor that is often compared with global OTT leaders like Netflix and Spotify. That’s because its three founders have been building Pocket FM on the back of technology, especially artificial intelligence (AI) and innovations, rather than just on content. Consider this: If you listen to the audio shows produced by Pocket FM, chances are you are listening to non-human voices, or voices generated or cloned by AI, narrating your favorite shows. Even the script of your favorite show might have been generated by AI tools. Global entertainment leaders like Netflix and Spotify are known for using AI for recommendations and personalization. Pocket FM took it one step further by placing AI at its core to enhance the user experience, expand reach, and even automate the creation of high-quality content for its listeners worldwide. The founders of Pocket FM have always been on the voyage of building a global entertainment platform that is powered by AI at an optimum level. To ensure global standards and follow best practices, the Indian startup has even poached Pannagadatta K Shivaswamy from Netflix, which is known for its personalized recommendations. Before joining Pocket FM, Shivaswamy was working as a machine learning (ML) research scientist at the company. Establishing partnerships to bolster AI One of Pocket FM’s recent AI initiatives is its partnership with New York-based voice technology research startup ElevenLabs. With this partnership, Pocket FM writers will now be able to create their own audio series—otherwise known as episodic audio shows—using the AI tools provided by ElevenLabs, including its text-to-voice feature. According to Pocket FM, these tools will allow its writers to transform their stories into immersive audio series in multiple languages to help reach a broader audience. As much as Pocket FM aims to democratize the modern approach to audio storytelling, its alliance with ElevenLabs will also help its team stay equipped with the necessary innovation for its planned global expansion. Over the next several years, Pocket FM plans to expand its audio series platform into new key consumer markets, starting with Europe and Latin America. At present, Pocket FM is a leader in India and the US. The need for extensive use of AI became prevalent as soon as Pocket FM entered its growth phase. Faced with increasing content consumption and diverse listener preferences, the Indian startup realized that traditional, manual processes were insufficient to sustain quality and scalability. With AI, Pocket FM has managed to automate and streamline operations, enhance personalization through sophisticated listener profiling, and maintain high-quality content across a vast array of audio files—but that’s not all. Pocket FM has been the power of AI for a whole host of things. Let’s take a look: AI-Powered Content Creation and Optimization AI-Generated Content: Pocket FM uses natural language processing (NLP) and generative adversarial networks (GANs) for content creation and optimization. This includes generating story plots, complex character development, and realistic voices through advanced text-to-speech (TTS) technology. This significantly reduces production time and costs while ensuring high-quality output. Localization: Pocket FM uses AI-driven neural machine translation (NMT) tools to adapt content across languages and regions, catering to its audience around the world. This automated localization ensures Pocket FM listeners worldwide get content that’s linguistically accurate and culturally relevant to their regions. Personalized User Experience AI-Powered Algorithms: Pocket FM uses AI algorithms, including collaborative filtering and deep learning models, to analyze user behavior, preferences, and listening patterns. This data-driven approach aims to tailor content delivery for every user according to their preferences so that average engagement increases. Monetization Strategies Targeted Advertising: AI-driven predictive analytics and ML models help the company hyper-target consumers with advertisements based on user preferences and listening habits. This, in turn, increases campaign effectiveness and maximizes revenue streams, reducing otherwise intrusive advertisements for the listeners. Additionally, AI employs clustering algorithms to identify user segments aiming to convert to paying users. Deep Learning Infrastructure: Pocket FM uses AI to process large volumes of audio files, ensuring high-quality content and automating the tagging and categorization process. This ensures smooth navigation and makes the discovery of content easy for listeners. Quality Assurance: AI technologies ensure consistent audio quality by automating quality checks and flagging any issues that need human review. Scalability Automated Content Management: AI-driven automation, including robotic process automation (RPA) and AI-based content curation, streamlines content management tasks. This allows Pocket FM to efficiently scale operations as it expands its content library and user base. Cost Optimisation: By leveraging AI for operational efficiency, including reducing the need for human intervention in repetitive tasks, Pocket FM significantly cuts down operational costs, enhancing its market competitiveness**.** Innovation and Future Prospects Continuous Improvement: AI continually learns and adapts, meaning that Pocket FM’s ability to recommend content, engage users, and optimize operations improves over time. As a result, its listeners receive enhanced quality of audio content that is easily accessible. Furthermore, Pocket FM frequently experiments with new content formats and interactive storytelling techniques driven by insights derived from AI analysis. Embracing the AI Revolution Although AI boasts several exciting capabilities, implementing it at scale across a company's functions comes with its own challenges. To avoid being overwhelmed, Pocket FM took a phased approach to AI implementation, starting with the integration of AI tools into smaller projects and gradually expanding their use across workflows, giving it enough scope to identify and resolve any issues early on to ensure a smoother transition. However, ensuring the consistency of high-quality data was one of the most significant challenges the India-based startup faced when integrating AI into its operations. “Training AI models on poor-quality data can lead to biased results, which we wanted to avoid,” Prateek Dixit, co-founder and CTO, said in a recent interview. “To address this, we invested heavily in cleaning and curating our data to maintain fairness and accuracy.” According to Dixit, Pocket FM also faced challenges in understanding this novel technology and its decision-making process. To manage that, the company developed human-in-the-loop systems that worked alongside the AI tools to optimally minimize possible errors. “At Pocket FM, we see AI as a powerful tool to not only enhance our operations but also fundamentally redefine the audio entertainment experience,” Dixit said in another interview. “Our future plans are focused on exploring new frontiers and pushing the boundaries of what’s possible with AI.” Dixit aims to ensure ethical AI practices within audio entertainment, with an emphasis on data privacy, fairness, and human oversight through responsible development. So far, Pocket FM’s integration of AI has been a game-changer. The future undoubtedly looks bright for AI in audio, with more and more collaborations that could bring innovations. As Dixit says, “Pocket FM’s aim is to leverage the power of AI to create a world where audio entertainment is not only enjoyable but also truly immersive, personalized, and accessible to all.” It’s a startup born out of dissatisfaction that cracked its product-market-fit primarily through remote work. It’s one that redefined entertainment—making it a more personal and on-the-go affair—by putting it into the pockets of millions of people worldwide, starting with India, where it started its journey in 2018. Pocket FM has been revolutionizing entertainment by making audio entertainment mainstream worldwide. Founded by Rohan Nayak, Prateek Dixit, and Nishanth KS, Pocket FM is known for its flagship audio series—serialized audio dramas presented in an episodic manner—which people across the globe pay to listen to. Pocket FM isn’t just another over-the-top (OTT) entertainment player with audio at its core. The startup is known for being a disruptor that is often compared with global OTT leaders like Netflix and Spotify. That’s because its three founders have been building Pocket FM on the back of technology, especially artificial intelligence (AI) and innovations, rather than just on content. Consider this: If you listen to the audio shows produced by Pocket FM , chances are you are listening to non-human voices, or voices generated or cloned by AI, narrating your favorite shows. Even the script of your favorite show might have been generated by AI tools. Pocket FM Pocket FM Global entertainment leaders like Netflix and Spotify are known for using AI for recommendations and personalization. Pocket FM took it one step further by placing AI at its core to enhance the user experience, expand reach, and even automate the creation of high-quality content for its listeners worldwide. The founders of Pocket FM have always been on the voyage of building a global entertainment platform that is powered by AI at an optimum level. To ensure global standards and follow best practices, the Indian startup has even poached Pannagadatta K Shivaswamy from Netflix, which is known for its personalized recommendations. Before joining Pocket FM, Shivaswamy was working as a machine learning (ML) research scientist at the company. Establishing partnerships to bolster AI One of Pocket FM’s recent AI initiatives is its partnership with New York-based voice technology research startup ElevenLabs. With this partnership, Pocket FM writers will now be able to create their own audio series—otherwise known as episodic audio shows—using the AI tools provided by ElevenLabs, including its text-to-voice feature. According to Pocket FM, these tools will allow its writers to transform their stories into immersive audio series in multiple languages to help reach a broader audience. As much as Pocket FM aims to democratize the modern approach to audio storytelling, its alliance with ElevenLabs will also help its team stay equipped with the necessary innovation for its planned global expansion. Over the next several years, Pocket FM plans to expand its audio series platform into new key consumer markets, starting with Europe and Latin America. At present, Pocket FM is a leader in India and the US. The need for extensive use of AI became prevalent as soon as Pocket FM entered its growth phase. Faced with increasing content consumption and diverse listener preferences, the Indian startup realized that traditional, manual processes were insufficient to sustain quality and scalability. With AI, Pocket FM has managed to automate and streamline operations, enhance personalization through sophisticated listener profiling, and maintain high-quality content across a vast array of audio files—but that’s not all. Pocket FM has been the power of AI for a whole host of things. Let’s take a look: AI-Powered Content Creation and Optimization AI-Generated Content: Pocket FM uses natural language processing (NLP) and generative adversarial networks (GANs) for content creation and optimization. This includes generating story plots, complex character development, and realistic voices through advanced text-to-speech (TTS) technology. This significantly reduces production time and costs while ensuring high-quality output. Localization: Pocket FM uses AI-driven neural machine translation (NMT) tools to adapt content across languages and regions, catering to its audience around the world. This automated localization ensures Pocket FM listeners worldwide get content that’s linguistically accurate and culturally relevant to their regions. AI-Generated Content: Pocket FM uses natural language processing (NLP) and generative adversarial networks (GANs) for content creation and optimization. This includes generating story plots, complex character development, and realistic voices through advanced text-to-speech (TTS) technology. This significantly reduces production time and costs while ensuring high-quality output. AI-Generated Content : Pocket FM uses natural language processing (NLP) and generative adversarial networks (GANs) for content creation and optimization. This includes generating story plots, complex character development, and realistic voices through advanced text-to-speech (TTS) technology. This significantly reduces production time and costs while ensuring high-quality output. AI-Generated Content Localization: Pocket FM uses AI-driven neural machine translation (NMT) tools to adapt content across languages and regions, catering to its audience around the world. This automated localization ensures Pocket FM listeners worldwide get content that’s linguistically accurate and culturally relevant to their regions. Localization : Pocket FM uses AI-driven neural machine translation (NMT) tools to adapt content across languages and regions, catering to its audience around the world. This automated localization ensures Pocket FM listeners worldwide get content that’s linguistically accurate and culturally relevant to their regions. Localization Personalized User Experience Personalized User Experience AI-Powered Algorithms: Pocket FM uses AI algorithms, including collaborative filtering and deep learning models, to analyze user behavior, preferences, and listening patterns. This data-driven approach aims to tailor content delivery for every user according to their preferences so that average engagement increases. AI-Powered Algorithms: Monetization Strategies Monetization Strategies Targeted Advertising: AI-driven predictive analytics and ML models help the company hyper-target consumers with advertisements based on user preferences and listening habits. This, in turn, increases campaign effectiveness and maximizes revenue streams, reducing otherwise intrusive advertisements for the listeners. Additionally, AI employs clustering algorithms to identify user segments aiming to convert to paying users. Deep Learning Infrastructure: Pocket FM uses AI to process large volumes of audio files, ensuring high-quality content and automating the tagging and categorization process. This ensures smooth navigation and makes the discovery of content easy for listeners. Quality Assurance: AI technologies ensure consistent audio quality by automating quality checks and flagging any issues that need human review. Targeted Advertising: AI-driven predictive analytics and ML models help the company hyper-target consumers with advertisements based on user preferences and listening habits. This, in turn, increases campaign effectiveness and maximizes revenue streams, reducing otherwise intrusive advertisements for the listeners. Additionally, AI employs clustering algorithms to identify user segments aiming to convert to paying users. Targeted Advertising: AI-driven predictive analytics and ML models help the company hyper-target consumers with advertisements based on user preferences and listening habits. This, in turn, increases campaign effectiveness and maximizes revenue streams, reducing otherwise intrusive advertisements for the listeners. Additionally, AI employs clustering algorithms to identify user segments aiming to convert to paying users. Targeted Advertising: Deep Learning Infrastructure: Pocket FM uses AI to process large volumes of audio files, ensuring high-quality content and automating the tagging and categorization process. This ensures smooth navigation and makes the discovery of content easy for listeners. Deep Learning Infrastructure : Pocket FM uses AI to process large volumes of audio files, ensuring high-quality content and automating the tagging and categorization process. This ensures smooth navigation and makes the discovery of content easy for listeners. Deep Learning Infrastructure Quality Assurance: AI technologies ensure consistent audio quality by automating quality checks and flagging any issues that need human review. Quality Assurance: AI technologies ensure consistent audio quality by automating quality checks and flagging any issues that need human review. Quality Assurance: Scalability Scalability Automated Content Management: AI-driven automation, including robotic process automation (RPA) and AI-based content curation, streamlines content management tasks. This allows Pocket FM to efficiently scale operations as it expands its content library and user base. Cost Optimisation: By leveraging AI for operational efficiency, including reducing the need for human intervention in repetitive tasks, Pocket FM significantly cuts down operational costs, enhancing its market competitiveness**.** Automated Content Management: AI-driven automation, including robotic process automation (RPA) and AI-based content curation, streamlines content management tasks. This allows Pocket FM to efficiently scale operations as it expands its content library and user base. Automated Content Management: AI-driven automation, including robotic process automation (RPA) and AI-based content curation, streamlines content management tasks. This allows Pocket FM to efficiently scale operations as it expands its content library and user base. Automated Content Management: Cost Optimisation: By leveraging AI for operational efficiency, including reducing the need for human intervention in repetitive tasks, Pocket FM significantly cuts down operational costs, enhancing its market competitiveness**.** Cost Optimisation: By leveraging AI for operational efficiency, including reducing the need for human intervention in repetitive tasks, Pocket FM significantly cuts down operational costs, enhancing its market competitiveness**.** Cost Optimisation: Innovation and Future Prospects Innovation and Future Prospects Continuous Improvement: AI continually learns and adapts, meaning that Pocket FM’s ability to recommend content, engage users, and optimize operations improves over time. As a result, its listeners receive enhanced quality of audio content that is easily accessible. Continuous Improvement: AI continually learns and adapts, meaning that Pocket FM’s ability to recommend content, engage users, and optimize operations improves over time. As a result, its listeners receive enhanced quality of audio content that is easily accessible. Continuous Improvement: Furthermore, Pocket FM frequently experiments with new content formats and interactive storytelling techniques driven by insights derived from AI analysis. Embracing the AI Revolution Although AI boasts several exciting capabilities, implementing it at scale across a company's functions comes with its own challenges. To avoid being overwhelmed, Pocket FM took a phased approach to AI implementation, starting with the integration of AI tools into smaller projects and gradually expanding their use across workflows, giving it enough scope to identify and resolve any issues early on to ensure a smoother transition. However, ensuring the consistency of high-quality data was one of the most significant challenges the India-based startup faced when integrating AI into its operations. “Training AI models on poor-quality data can lead to biased results, which we wanted to avoid,” Prateek Dixit, co-founder and CTO, said in a recent interview . “To address this, we invested heavily in cleaning and curating our data to maintain fairness and accuracy.” recent interview recent interview According to Dixit, Pocket FM also faced challenges in understanding this novel technology and its decision-making process. To manage that, the company developed human-in-the-loop systems that worked alongside the AI tools to optimally minimize possible errors. “At Pocket FM, we see AI as a powerful tool to not only enhance our operations but also fundamentally redefine the audio entertainment experience,” Dixit said in another interview . “Our future plans are focused on exploring new frontiers and pushing the boundaries of what’s possible with AI.” another interview another interview Dixit aims to ensure ethical AI practices within audio entertainment, with an emphasis on data privacy, fairness, and human oversight through responsible development. So far, Pocket FM’s integration of AI has been a game-changer. The future undoubtedly looks bright for AI in audio, with more and more collaborations that could bring innovations. As Dixit says, “Pocket FM’s aim is to leverage the power of AI to create a world where audio entertainment is not only enjoyable but also truly immersive, personalized, and accessible to all.”