Mple.ai - TechStoriess.com

Welcome to TechStoriess. Today, we sit down with Ameet Verma, Co-Founder and CEO of mple.ai, to discuss the future of frontline workforce enablement. Drawing from a 20-year tenure at Microsoft, Ameet recognized a critical flaw in traditional corporate training: it was entirely passive. Employees were consuming content but hesitating during high-stakes customer interactions—much like trying to learn to swim just by reading a book. Enter mple.ai, a platform designed to bridge this gap through AI-driven conversational simulations. By allowing professionals in BFSI, Pharma, and Retail to practice real-world scenarios in a safe environment, mple.ai is transforming passive "learning hours" into hard business metrics like sales growth and reduced employee churn. In this interview, Ameet shares the breaking point that inspired his startup, his vision for AI as a daily co-pilot, and how building muscle memory is the ultimate key to unlocking frontline confidence. What was the specific “breaking point” in traditional workforce training that convinced you mple.ai was a necessity? The real breaking point for me came when I realized that most corporate training was being completed but not truly applied. I remember speaking with a sales leader in a large pharmaceutical company. He told me something very simple but very honest. “My team finishes all the training modules, but when they meet doctors, the conversation still becomes difficult.” That moment made me think deeply. It reminded me of learning to swim. You can read about swimming, watch videos, and understand every technique. But until you enter the water, you never really learn. Traditional workforce training was very similar. People were consuming content, but they were not practicing real situations. That is where the idea of mple AI came from. We wanted to create a space where professionals could practice real conversations before they face real customers. When people practice in a safe environment, confidence grows. And confidence is what truly changes performance in the real world. How did your 20-year tenure at Microsoft specifically define mple AI’s approach to enterprise-scale AI? My years at Microsoft shaped one very important belief that we follow strongly at mple AI. Technology only matters if it solves a real problem at scale. At Microsoft, I saw how products were built not just for a few users but for millions of people across organizations. That mindset stayed with me. Enterprise technology has to be simple, reliable and capable of working across thousands of employees without becoming complicated. I also learned that adoption is more important than features. Many companies buy powerful systems, but if employees do not use them daily, the impact remains limited. We designed mple AI with that thinking. It should feel as simple as sending a message or having a conversation. For example, a sales representative should be able to practice a customer conversation in minutes, just like rehearsing before an important meeting. Enterprise AI should not feel like heavy technology. It should quietly support people and help them perform better every day. Beyond the tech, what is the personal mission that drives you to focus specifically on “frontline” enablement? For me, the motivation is very personal. In most organizations, the frontline teams are the ones who actually carry the brand to the customer. Sales representatives, service staff, medical representatives, relationship managers. They are the people who face real questions, real objections, and real pressure every day. Yet they are often the ones who receive the least practical support. I have met many talented professionals who know their work well but hesitate in critical moments because they did not get enough opportunity to practice. A medical representative meeting a senior doctor or a young sales executive speaking to a large client can feel the same nervousness a student feels before an exam. My mission is to help remove that hesitation. If we can give frontline teams a safe place to practice conversations, learn from mistakes, and build confidence, their entire performance changes. When confidence improves, customer conversations improve, outcomes improve, and people start enjoying their work more. That transformation is what drives me every day. Conventional training is often passive; how do your AI simulations physically change the way a field agent performs under pressure? Traditional training is mostly passive. People watch a video, attend a session, or read material. They understand the theory, but when they face a real customer, the pressure is very different. What changes with AI simulations is practice. Just like an athlete prepares before a match, professionals need to rehearse real situations. With mple AI, a field agent can practice conversations with an AI doctor, customer, or client that behaves like a real person. The AI asks questions, raises objections, and sometimes challenges the explanation. The agent has to respond in real time. This repetition builds muscle memory. The first attempt may be hesitant, the second becomes better, and by the fifth or sixth attempt the agent becomes much more confident. Think of it like rehearsing before a presentation. When you practice multiple times, the actual moment feels familiar instead of stressful. That is the shift we create. Instead of just learning what to say, field teams experience how to say it confidently when it matters most. How does mple AI turn “learning hours” into hard business metrics like sales growth or reduced churn? For many years companies measured training by the number of hours completed. But hours spent learning do not always translate into better performance. At mple AI we focus on the moments that truly impact business outcomes. For example, in pharma sales the real challenge is not knowing the product slide but handling a doctor’s question during a short meeting. When medical representatives repeatedly practice these conversations through AI simulations, they become clearer, faster, and more confident. That confidence improves doctor engagement and prescription adoption. In studies we have conducted with large global companies, we have seen a strong correlation between time spent in skill practice and improvements in sales performance and revenue outcomes. Another important impact is on employee retention. Many employees leave not because of the job itself but because they do not feel confident or purposeful in their role. When teams feel capable and prepared for real conversations, their sense of purpose increases. Confidence grows, performance improves, and organizations see lower churn along with stronger business results. Between BFSI, Retail, and Pharma, where are you seeing the fastest adoption of AI coaching in the Indian market? In India today, we’re seeing the fastest adoption of AI coaching in BFSI, followed by pharma and then retail. BFSI is leading the way due to its strong digital foundation and the growing pressure to enhance customer experience, manage risk, and compete with fintech disruptors. With frontline teams engaging customers daily, banks and financial institutions are investing heavily in AI-driven training to enable faster, more confident interactions. Pharma is close behind, where adoption is accelerating rapidly. Medical representatives operate in high-stakes, time-constrained environments, making AI simulations invaluable for practicing scientific conversations and handling objections effectively. Retail is also gaining momentum, particularly among store associates and customer service teams, where consistent, high-quality interactions directly impact sales. Across industries, a clear shift is emerging: organizations increasingly recognize that frontline conversations shape business outcomes. As a result, investing in AI coaching for these teams is becoming one of the fastest and most effective ways to drive measurable impact. Can you share insights into your current funding status and how you are prioritizing capital allocation for R&D? We have recently raised a pre seed round with a couple of institutional funds along with some foreign direct investors. This has given us strong validation that the problem we are solving is real and global in nature. Our focus right now is very clear. We are investing most of our capital into two important pillars of mple AI which are customer experience and product innovation. On the product side, a significant portion of our investment goes into research and development. We are continuously improving our AI simulations so that they behave more like real conversations. The goal is to make practice feel as close as possible to real customer interactions. The second pillar is customer experience. Enterprise technology often becomes complex for users. We are focused on making the platform omnichannel so that users can have the same learning and practice experience across different platforms whether it is mobile, web, or messaging environments. For us, innovation is meaningful only when it solves real problems for people on the ground. That principle guides how we invest every rupee into building mple AI as a global capability platform. While keeping specifics private, what has been the most significant driver of your revenue growth over the past year? The most significant driver of our revenue growth over the past year has been customer belief and trust. A large part of our growth has come through references and word of mouth rather than traditional selling. Our clients are experts in their industries, whether it is pharma, BFSI, or retail. Instead of building products in isolation, we work closely with them, understand their day to day challenges, and co create solutions together. We are also expanding learning beyond just mobile screens by enabling it through multiple channels, adding more versatility to the learning journey. This allows professionals to practice and learn in the flow of their daily work rather than only through a traditional training format. When customers see that their feedback directly shapes the product, their belief in the platform grows. That trust naturally turns into references and word of mouth, which has been the strongest driver of our growth. By 2030, do you believe “manual” training will be obsolete for distributed workforces, or will AI always remain a co-pilot? By 2030, I do not believe manual training will completely disappear. Learning is a human experience and there will always be value in human mentors, managers, and peer learning. What will change is how much of the repetitive and scalable part of training is handled by AI. AI will increasingly act as a co pilot that helps employees practice, learn, and get feedback anytime they need. For distributed workforces especially, waiting for classroom sessions or periodic workshops is no longer practical. Think of it like how GPS works today. We still know how to drive, but GPS helps us navigate faster and avoid mistakes. In the same way, AI will guide employees through practice, feedback, and continuous improvement. Human leaders will still play a critical role in coaching, motivation, and culture building. AI will simply make learning more continuous, accessible, and personalized. The future of workforce development will not be human versus AI. It will be human capability amplified by AI. What is the “North Star” goal for mple AI as you look toward global expansion and product evolution? The North Star for mple AI is simple: to help millions of frontline professionals feel confident in the moments that matter most. Across industries and geographies, the underlying challenge is remarkably consistent. Whether it’s a sales representative meeting a doctor, a banker advising a customer, or a retail associate explaining a product, these brief interactions often determine business outcomes. When people feel prepared, the quality of these conversations—and their impact—changes dramatically. As we expand globally, our goal is to build a platform that enables professionals to continuously practice real-world scenarios and improve their capabilities every day. At the product level, we envision mple.ai as a global capability engine: one that helps organizations build confident, high-performing teams at scale. This means constantly evolving the platform to be more intelligent, more accessible across channels, and more reflective of real-life work situations.

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Interview : Replacing Passive Corporate Training with AI-Powered Conversation Practice – Mple.ai

Interview : Replacing Passive Corporate Training with AI-Powered Conversation Practice – Mple.ai

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