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No Priors: Artificial Intelligence | Technology | Startups

Building an Autonomous Enterprise for Real-World Services with Netic Founder Melisa Tokmak

34 min episode · 2 min read
·
Netic Founder Melisa Tokmak

Episode

34 min

Read time

2 min

Topics

Career Growth, Productivity, Health & Wellness

AI-Generated Summary

Key Takeaways

  • AI-First Adoption Rate: Over 70% of Netic's enterprise customers have gone fully "Netic-first," meaning every initial customer interaction is handled by AI agents rather than humans. This shift from overflow support to primary interface represents a fundamental operational restructuring, not incremental automation, and has generated over $600 million in revenue for customers through AI-handled interactions.
  • Essential Services Complexity: Deploying AI in HVAC or plumbing requires resolving multiple variables simultaneously — unit type, customer lifetime value, technician specialization, and scheduling urgency — before dispatching labor. Businesses targeting this space must build orchestration layers, domain-specific harnesses, and vertical software on top of foundation models; raw model capability alone cannot address this operational depth.
  • Rollup vs. Platform Trade-off: Founders choosing between AI-enabled rollups and vertical software platforms should assess whether their core skill is M&A or product building. Rollup products serve only acquired companies and cannot compound across industries, while a platform approach allows the same intelligence layer to serve thousands of businesses, creating scalable network effects and compounding data advantages.
  • Screening for Agency in Hiring: Rather than asking about recent work achievements, probe a candidate's entire life history for sustained, self-initiated effort. Ask what the hardest thing they have ever done is, then dig into the why. The signal is not one dramatic example but a consistent pattern across years of starting things independently and following through without external pressure.
  • Private Equity AI Misconception: PE firms default to framing AI as a cost-cutting tool because they rarely encounter platforms that generate net-new revenue. When selling AI into PE-owned portfolios, lead with live deployment data showing incremental revenue generated — not demos — and explicitly reframe the conversation from margin compression to new customer acquisition and cross-portfolio service bundling opportunities.

What It Covers

Melisa Tokmak, founder of Netic, explains how her company deploys AI agents to run autonomous enterprise operations for billion-dollar home services, HVAC, pet care, and wellness companies — handling all customer interactions, scheduling, and labor dispatch so businesses can focus entirely on service delivery.

Key Questions Answered

  • AI-First Adoption Rate: Over 70% of Netic's enterprise customers have gone fully "Netic-first," meaning every initial customer interaction is handled by AI agents rather than humans. This shift from overflow support to primary interface represents a fundamental operational restructuring, not incremental automation, and has generated over $600 million in revenue for customers through AI-handled interactions.
  • Essential Services Complexity: Deploying AI in HVAC or plumbing requires resolving multiple variables simultaneously — unit type, customer lifetime value, technician specialization, and scheduling urgency — before dispatching labor. Businesses targeting this space must build orchestration layers, domain-specific harnesses, and vertical software on top of foundation models; raw model capability alone cannot address this operational depth.
  • Rollup vs. Platform Trade-off: Founders choosing between AI-enabled rollups and vertical software platforms should assess whether their core skill is M&A or product building. Rollup products serve only acquired companies and cannot compound across industries, while a platform approach allows the same intelligence layer to serve thousands of businesses, creating scalable network effects and compounding data advantages.
  • Screening for Agency in Hiring: Rather than asking about recent work achievements, probe a candidate's entire life history for sustained, self-initiated effort. Ask what the hardest thing they have ever done is, then dig into the why. The signal is not one dramatic example but a consistent pattern across years of starting things independently and following through without external pressure.
  • Private Equity AI Misconception: PE firms default to framing AI as a cost-cutting tool because they rarely encounter platforms that generate net-new revenue. When selling AI into PE-owned portfolios, lead with live deployment data showing incremental revenue generated — not demos — and explicitly reframe the conversation from margin compression to new customer acquisition and cross-portfolio service bundling opportunities.

Notable Moment

Tokmak reframes the "can the big labs do this?" concern by comparing it to the decade-old "can Google do this?" anxiety. She argues that labs optimizing for generalizability treat vertical, mission-critical workflow problems as intellectually beneath their focus, which structurally protects specialized enterprise AI builders.

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Episode Transcript

Today on our priors, we're joined by Melissa Tocmac. Melissa is the founder and CEO of NetIQ, a company that builds AI for different real world services like HVAC, pet care, a variety of other things like that, roofers. Prior to NetIQ, Melissa was a director of engineering and worked on various aspects of go to market for scale dot ai and, also has experiences from Meta. Welcome to NoPrize, Melissa. Melissa, thanks for joining us today at NoPrize. Thank you for having me. Yeah. Maybe we can start off by talking a little bit about your business and what you're building because I think that, you're doing something really interesting in the real world and you're kinda mirroring AI in the real world. So could you tell us more about your company and NetIQ and, you know, what you're focused on? Yeah. NetIQ builds AI to run millions of real world businesses that keep the world running. That means, basically, we work with large enterprises in essential services. We started in essential services. What would be an example of essential service? Imagine a billion dollar revenue home services companies in HVAC, plumbing, electric, or consumer wellness companies, like, where you can become a member and really go do a lot of sports or different activities, hospitality, automotive, pet services across the board. So every single thing that you need to run your life or that you want to do, are a good example. And a lot of these businesses are actually quite large businesses, and they interact with millions of end users themselves, usually that are consumers or businesses themselves. So NetIQ exists between the company and its customers. So every single thing to understand the customer need or want and match that with how can we even help the customer with the operational rules of the business and even deploy the services or the labor all happens on NetIQ. So, basically, say a customer calls an HVAC provider. What what happens or what is NetIQ doing for them? Yeah. So imagine that you are in the middle of nowhere, it's minus 20 degrees, and your heat stops working. So you first find, right, a provider. And there are many providers. You wanna pick the most trustworthy one and the one that you can get to because you're in a minus 20 degree weather. Maybe you have a kid or an elderly or something is not working. From there, once you find a business and usually you can find these from aggregators or by search engines or in now LLMs, and you can reach out to the company from any medium you want. If they're using NetIQ, you can call them or text them or find an like, go to their website to general nine scheduler. It's NetIQ agents that talk to the customer. What kind of home do you live in? Do we have any of your records? As you said, this could be like a voice call. …

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