Steve welcomes Thomas Rivera, Founding Partner of NLPearl, for a conversation that might fundamentally change how you think about customer service infrastructure. With over two and a half years building AI voice solutions for major e-commerce platforms, Thomas brings the kind of practical implementation knowledge that turns “interesting technology” into actual revenue protection.

The episode opens with a sobering reality check: that phone number on your website is probably your biggest conversion killer. Whether it’s routing to someone’s personal cell (and going to voicemail when they’re unavailable) or connecting to an outsourced call center that feels disconnected from your brand, most Shopify stores have a fragmented phone experience that loses customers before they even make a purchase. Thomas explains how NLPearl saw this gap after working with enterprise e-commerce platforms—the phone was consistently the weakest link in an otherwise optimized tech stack.

Here’s what makes this episode immediately actionable: Thomas walks through exactly how NLPearl’s AI voice agent works in the Shopify ecosystem. The platform integrates directly with your store’s backend, pulling real-time data on orders, inventory, SKU details, shipping information, and return policies. When a customer calls asking “Where’s my order?” or “Do you have this in size medium?” the AI agent retrieves the answer from your actual Shopify data and responds in a natural, conversational voice—no scripted robotic responses, no frustrating menu trees.

The setup process is almost shockingly simple. Install the app from the Shopify app store, let it ingest your store data (which happens automatically), configure a few preferences, and within 5-10 minutes you have a fully functional 24/7 front desk that never sleeps, never takes vacation, and handles multiple calls simultaneously. Pricing starts at $49/month for smaller stores, with plans scaling to $99/month, $199/month, and $299/month based on concurrent call capacity—a fraction of what you’d pay for even part-time call center coverage.

You’ll hear Thomas address the obvious concern: what about the human touch? The smart implementation isn’t replacing your team entirely—it’s using AI as an intelligent triage system. The agent handles routine queries 24/7 (order status, return policies, product availability), and during business hours when live agents are available, it can seamlessly transfer more complex conversations that need that personal connection. This hybrid approach gives you round-the-clock coverage without sacrificing the relationship-building moments that matter most.

The conversation covers voice customization (you can choose male or female voices, different accents, speaking styles that match your brand), how the system handles abandoned cart recovery, why concurrent call capacity matters during flash sales and peak periods, and the real ROI calculation—not just cost savings versus call centers, but the revenue you capture from customers who would have otherwise bounced to voicemail and never returned. This isn’t theory or future speculation—it’s infrastructure that’s working right now, with a seven-day free trial that lets you test it risk-free with your actual store data and customer calls.

👉  Treat your phone number like the revenue channel it actually is, not an afterthought. Right now, most Shopify stores either route calls to someone’s personal cell or pay thousands for disconnected call center staff. The phone is where high-intent customers go when they’re ready to buy but need a quick answer—treating it like a second-tier channel means watching 80% of those callers walk away to competitors when they hit voicemail. Whether you’re doing $50K or $5M annually, every missed call is leaked revenue you’ve already paid to acquire.

👉  Start with the 24/7 coverage that AI provides, then layer in human touchpoints strategically. The most effective implementation isn’t “AI or humans”—it’s AI as your front desk handling routine queries around the clock, with seamless transfers to live agents during business hours for complex situations. This gives smaller stores enterprise-level availability without the enterprise budget, and gives larger operations the ability to scale call handling during peak periods without adding headcount. Set up the AI to manage order status, shipping questions, return policies, and product availability, then train it to recognize when to hand off to a human for nuanced customer service moments.

👉  Use the seven-day free trial to test with real calls and real data, not hypothetical scenarios. Install NLPearl from the Shopify app store, let it ingest your actual store information, deploy the number on your site, and watch how it handles genuine customer inquiries with your specific products, policies, and order data. Run it parallel to your existing phone setup for a week—forward some calls to the AI, some to your current system, and compare response quality, resolution rates, and customer feedback. The only way to know if this technology works for your specific use case is to test it with your actual customers asking your actual questions.

👉  Calculate ROI based on recovered revenue, not just cost savings. Yes, $49-299/month is dramatically cheaper than call center staff at $3,000+ monthly. But the real value isn’t what you save—it’s what you capture. If your average order value is $150 and the AI agent converts just three customers weekly who would have otherwise hit voicemail and bounced, that’s $1,800/month in recovered revenue from a $49 investment. Track how many calls come in after hours, how many go to voicemail currently, and what percentage of those callers are likely ready to buy. Track calls that come in outside business hours separately—these represent pure incremental revenue since they would have been lost completely without AI coverage. That math changes fast when you realize you’re not just cutting costs—you’re plugging a revenue leak.

👉  Configure voice and personality to match your brand positioning, not just default settings. The technology now supports different voices (male/female), accents, speaking speeds, and conversational styles. If you’re a premium fashion brand, your AI agent should sound polished and sophisticated. If you’re a casual lifestyle brand, it should feel approachable and friendly. Take the time during setup to test different voice options, listen to how the agent introduces your brand, and adjust the tone to match the customer experience you’ve built everywhere else. Voice is intimate—make sure it reinforces your brand identity rather than creating disconnect.

👉  Build concurrent call capacity into your growth planning from day one. One of the hidden bottlenecks in scaling is what happens when multiple customers try to call simultaneously—during flash sales, product drops, or holiday peaks. Traditional solutions mean paying per additional seat or accepting that some callers get busy signals. AI voice agents can handle 10, 15, or 20 concurrent calls depending on your plan tier, which means your phone infrastructure scales automatically with traffic spikes. Choose your plan based not just on average daily call volume, but on peak capacity during your busiest selling periods—Black Friday, Cyber Monday, or whenever you run major promotions that drive phone inquiries.

Thomas Rivera
Founding Partner, NLPearl

Thomas Rivera is the Founding Partner of NLPearl, an AI voice agent platform that’s been solving customer service challenges for over two and a half years across multiple industries. Before bringing the technology to Shopify, NLPearl built solutions for major ecommerce platforms (under NDA), hospitality operations, airlines, government agencies, real estate firms, and legal practices—gaining deep expertise in how AI voice technology needs to adapt across vastly different customer service contexts.

What makes Thomas’s perspective valuable isn’t just the technical sophistication of the platform—it’s his understanding of where phone systems break down in the e-commerce journey. He watched countless Shopify stores struggle with fragmented phone experiences: small operations routing calls to personal cell phones that go to voicemail during off-hours, mid-market brands paying thousands monthly for outsourced call centers that feel disconnected from the brand, and larger operations forcing customers through frustrating IVR menus that create abandonment before anyone even reaches a human. He saw the phone consistently being the weakest link in otherwise well-optimized tech stacks.

That insight led to NLPearl’s Shopify integration—a solution purpose-built for e-commerce that connects directly to store backends, pulls real-time order and inventory data, and delivers natural conversational experiences without the robotic scripting that plagued earlier voice automation attempts. Thomas and his team focused obsessively on reducing setup friction (the entire implementation takes 5-10 minutes) and pricing accessibility (plans start at $49/month versus $3,000+ for traditional call centers), making enterprise-level phone infrastructure available to stores at every revenue stage.

His approach reflects the practical realities of running e-commerce operations: AI shouldn’t replace human touchpoints entirely, but should handle the high-volume routine queries that drain team bandwidth while seamlessly transferring complex situations to live agents. It’s infrastructure that scales with growth, handles concurrent calls during peak periods, and turns the phone from a cost center or neglected channel into an actual revenue driver that captures customers who would otherwise vanish to voicemail and never return.