Payoda Technologies Gearing to Transform the Telecommunications Sector Using AI
The telecommunications sector is one of the fields identified as being ripe for disruption by artificial intelligence and machine learning. From light models being deployed at the edge, to AI-powered spam filters, to scam prevention by using machine learning algorithms—emerging technologies can be deployed to great efficacy in telecom. Among the companies that are making strides in bringing AI and ML to the edge is Payoda Technologies. Established in 2005, this company is now in its growth phase, planning to double its workforce by 2025 in anticipation of the blossoming telecom market in India. To gain more insight into how the company is offering these unique solutions to their customers, Analytics India Magazine reached out to Karunya Sampath, Co-founder & CEO, Payoda Technologies. Innovative use cases of AI in telecommunication The telecom sector has a rich treasure trove of data that can be used to detect patterns. Sampath said, “By understanding advanced patterns within data, one can detect and predict network anomalies. Acting swiftly, it fixes the problems before the customers start getting affected.” As the telecom sector is one of the prime spaces to apply AI and ML, Payoda is able to deploy unique solutions tailored for their clients’ use cases. They have created a digital assistant for telecom firms, which has enabled personalised and guide line-based responses through multiple conversational channels. On this, Sampath remarked, “With a comprehensive AI-assisted, personality-based linguistic solution, the conversation happens in natural language, but in an easy to understand synthetic voice.” Payoda also offers a smart call centre service for telcos, which utilises intelligent routing and analytics, thus offering better market insights for newer products. Speaking on the virtual assistant, Sampath said, “The virtual assistant with in-built memory leads to indirect business benefits like omni-channel customer experience, leading to improved customer response time along with brand consistency.” Payoda’s AI solutions Payoda has created a technology suite for AI-enabled call centres to enable quick problem resolution and communication with customers across time periods. Primarily, the suite records all calls to help with future reference. It also has a main-built dashboard which can be used for data analytics. The AI secret sauce comes in the form of built-in sentiment analysis that works in real time to capture the customer’s real time emotions. In addition to this, there is also an ‘Agent Coach’ that helps customer service executives to improve customer service and gives real time suggestions to enable a quicker resolution of the customer’s problems. For certain newer products, the AI also has access to market insights, allowing agents to easily upsell or cross-sell to the end user. All these services are also easily scalable and can provide even more features. On the personalised AI solutions, Sampath stated, “Hyper personalisation through voice analytics and enterprise dashboards for workforce optimisation help in business retention through intelligent customer engagement and serves as a channel to increase new business.” AI in fraud management systems The data which is collected by Payoda’s AI solutions is then monitored, analysed, and correlated every hour over a period of month, resulting in a consolidated dataset. The data is then provided to the management, allowing them to root out possible fraudulent activities and figure out their scam cycles. This then helps brands maintain their brand identity while providing a safer experience for the customers. On the issues faced while training the AI, Sampath said, “Typical Anomaly Detection Challenges can be interpreted with data imbalance issues. Oversampling or under-sampling is the perfect solution on a case-to-case basis.” Other areas that AI can be applied in the telecom sector On the scope of AI services in the telecom sector, Sampath remarked “The telecommunication market in itself is vast and has huge potential for using AI-based solutions. Payoda sees a great opportunity in Network Optimization through planning, predictive network maintenance and network upgrades.” Network monitoring and related analytical tasks will be crucial to extract the most value from these services. This will have second and third order effects that will trickle down to provide overall efficiency gains to the company. Payoda is also aiming to target the customer engagement space as a way to inject AI into various facets of the telecom sector. The usage of AI as a customer agent has already proved to be a huge value add for the telecom sector. Speaking on AI conversational agents, Sampath stated, “Today, efficient customer support operations are possible all thanks to AI as a customer agent and AI-powered customer communication. This results in accurate product recommendations and a fully automated call centre.” Payoda’s solutions also help in app governance, brand unification, and AI enabled operations such as noise suppression, anomaly detection, and correlation. How AI can change the telecom landscape The company has seen phenomenal benefits to their customers after deploying smart technologies. From reducing the workload of traditional customer executive agents, to cutting down time wasted on data collection, to increasing resolution rates of customers—smart technologies can provide huge optimisations for companies. Advances in conversational AI, automation, and AI-powered digital agents have witnessed wide adoption in the telecom sector. Speaking on these innovations, Sampath stated, “These AI powered customer communications give accurate product recommendations and have multiple channels to reach out to customers like mobile, chat and SMS. There is no limit to the potential of AI, all we need to do is tap in.”
“There is no limit to the potential of AI, all we need to do is tap in.”
“There is no limit to the potential of AI, all we need to do is tap in.”
["AI (Artificial Intelligence)", "Interviews and Discussions"]
["machine learning", "artificial intelligence", "AI", "sentiment analysis", "ML", "Aim", "anomaly detection", "analytics", "conversational agents", "R", "AI (Artificial Intelligence)", "Interviews and Discussions"]
["AI", "artificial intelligence", "machine learning", "ML", "analytics", "conversational agents", "Aim", "anomaly detection", "sentiment analysis", "R"]
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