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Conversational Intelligence: The Next Big Thing In Customer Experience

2 minutes 30 seconds read

Conversational AI is the technology that makes human-computer conversations emotionally intelligent, and less scripted. It allows AI-led chatbots to interact with people in a human-like manner, thereby keeping this human-computer interaction as natural as possible, yet high on its emotional quotient.

Conversational AI is trained to comprehend and engage in contextual dialogue using Natural Language Processing (NLP) and additional AI algorithms.

Conversational AI is one among a few other new-age technologies that continue to emerge on the scene including augmented intelligence, edge AI, data labeling, and explainable AI.

How Conversational AI helps with better CX? 

Conversational AI uses a combination of natural language processing (NLP), machine learning (ML), speech recognition, natural language understanding (NLU), among other language technologies to process and contextualize voice or text messages and accordingly respond with the most suitable answer. 

Through NLP, the computer can ascertain the intents and entities of the customer on the other end, while identifying statistically significant patterns that it has been trained on. This enables it to learn your business needs and get smarter with time, thus helping a more evolved customer experience. 

Why is it important to invest in Conversational AI?

Gartner had predicted that, by the year 2020, customers would manage 85% of their interactions with businesses without interacting with a human. It’s predicted that in the upcoming decade, basic automation and apps will be replaced with advanced AI technologies with an objective to improve the overall customer experience metric by proactively gauging the customer’s needs and intent and engaging on an emotional level. 

An increased amount of AR and VR innovations across industries are set to be the norm by 2025 as part of an expected customer experience offering. 

“The greatest advantage of having a conversational AI solution is the instant response rate. Answering inquiries within an hour means 7X greater probability of converting over a lead. Clients are bound to discuss a negative encounter than a positive one,” reports AnalyticsInsight.net. 

Image Courtesy: www.kore.ai

Conversational AI in Insurance 

Conversational AI is an ideal addition for service, healthcare, insurance organizations to name a few, as it helps with helping support agents streamline their work, take after-call notes in the CRM system, or complete the missing details that will help by building a seamless customer service system. The technology also helps predict or react to changing call patterns and/or any real-time guidance the agent might require. 

Additionally, customers can first engage in self-service aided by conversational intelligence to save time, improve efficiency and get the desired results sooner. While rebranding Care Health Insurance’s (erstwhile Religare) website and app, Mantra Labs deployed Hitee, their AR-based virtual support that helped with the first-level solution for the customer and in turn, led to higher New Business Conversions by a factor of 10X and an overall drop in customer queries over voice support by 20%.  

2021 Customer Support Trends Report says that inferior customer experience costs companies at least $62 billion annually. 56% of support leaders shared that their current chatbot implementations don’t carry intelligent tools in this report, and customers are increasingly demanding convenience from businesses they interact with. 

Intelligent chatbots make apps simple, and more human to use. Their USP is to create device-agnostic experiences across channels, thus becoming a key factor in driving intelligent customer experiences. 

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Why Netflix Broke Itself: Was It Success Rewritten Through Platform Engineering?

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Let’s take a trip back in time—2008. Netflix was nothing like the media juggernaut it is today. Back then, they were a DVD-rental-by-mail service trying to go digital. But here’s the kicker: they hit a major pitfall. The internet was booming, and people were binge-watching shows like never before, but Netflix’s infrastructure couldn’t handle the load. Their single, massive system—what techies call a “monolith”—was creaking under pressure. Slow load times and buffering wheels plagued the experience, a nightmare for any platform or app development company trying to scale

That’s when Netflix decided to do something wild—they broke their monolith into smaller pieces. It was microservices, the tech equivalent of turning one giant pizza into bite-sized slices. Instead of one colossal system doing everything from streaming to recommendations, each piece of Netflix’s architecture became a specialist—one service handled streaming, another handled recommendations, another managed user data, and so on.

But microservices alone weren’t enough. What if one slice of pizza burns? Would the rest of the meal be ruined? Netflix wasn’t about to let a burnt crust take down the whole operation. That’s when they introduced the Circuit Breaker Pattern—just like a home electrical circuit that prevents a total blackout when one fuse blows. Their famous Hystrix tool allowed services to fail without taking down the entire platform. 

Fast-forward to today: Netflix isn’t just serving you movie marathons, it’s a digital powerhouse, an icon in platform engineering; it’s deploying new code thousands of times per day without breaking a sweat. They handle 208 million subscribers streaming over 1 billion hours of content every week. Trends in Platform engineering transformed Netflix into an application dev platform with self-service capabilities, supporting app developers and fostering a culture of continuous deployment.

Did Netflix bring order to chaos?

Netflix didn’t just solve its own problem. They blazed the trail for a movement: platform engineering. Now, every company wants a piece of that action. What Netflix did was essentially build an internal platform that developers could innovate without dealing with infrastructure headaches, a dream scenario for any application developer or app development company seeking seamless workflows.

And it’s not just for the big players like Netflix anymore. Across industries, companies are using platform engineering to create Internal Developer Platforms (IDPs)—one-stop shops for mobile application developers to create, test, and deploy apps without waiting on traditional IT. According to Gartner, 80% of organizations will adopt platform engineering by 2025 because it makes everything faster and more efficient, a game-changer for any mobile app developer or development software firm.

All anybody has to do is to make sure the tools are actually connected and working together. To make the most of it. That’s where modern trends like self-service platforms and composable architectures come in. You build, you scale, you innovate.achieving what mobile app dev and web-based development needs And all without breaking a sweat.

Source: getport.io

Is Mantra Labs Redefining Platform Engineering?

We didn’t just learn from Netflix’s playbook; we’re writing our own chapters in platform engineering. One example of this? Our work with one of India’s leading private-sector general insurance companies.

Their existing DevOps system was like Netflix’s old monolith: complex, clunky, and slowing them down. Multiple teams, diverse workflows, and a lack of standardization were crippling their ability to innovate. Worse yet, they were stuck in a ticket-driven approach, which led to reactive fixes rather than proactive growth. Observability gaps meant they were often solving the wrong problems, without any real insight into what was happening under the hood.

That’s where Mantra Labs stepped in. Mantra Labs brought in the pillars of platform engineering:

Standardization: We unified their workflows, creating a single source of truth for teams across the board.

Customization:  Our tailored platform engineering approach addressed the unique demands of their various application development teams.

Traceability: With better observability tools, they could now track their workflows, giving them real-time insights into system health and potential bottlenecks—an essential feature for web and app development and agile software development.

We didn’t just slap a band-aid on the problem; we overhauled their entire infrastructure. By centralizing infrastructure management and removing the ticket-driven chaos, we gave them a self-service platform—where teams could deploy new code without waiting in line. The results? Faster workflows, better adoption of tools, and an infrastructure ready for future growth.

But we didn’t stop there. We solved the critical observability gaps—providing real-time data that helped the insurance giant avoid potential pitfalls before they happened. With our approach, they no longer had to “hope” that things would go right. They could see it happening in real-time which is a major advantage in cross-platform mobile application development and cloud-based web hosting.

The Future of Platform Engineering: What’s Next?

As we look forward, platform engineering will continue to drive innovation, enabling companies to build scalable, resilient systems that adapt to future challenges—whether it’s AI-driven automation or self-healing platforms.

If you’re ready to make the leap into platform engineering, Mantra Labs is here to guide you. Whether you’re aiming for smoother workflows, enhanced observability, or scalable infrastructure, we’ve got the tools and expertise to get you there.

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