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

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

No Priors•34:30•2026-07-31•Source Audio
Host
Elad Gil
Guests
Melisa Tokmak

Executive Summary

Netic founder Melisa Tokmak describes building an AI product for essential real-world service businesses, choosing a scalable platform rather than an acquisition roll-up, and viewing the next phase of AI adoption through operations, measurable ROI, and human-delivered services.

Chapters & Key Takeaways

Netic is described as an operational intermediary that can handle customer interaction and coordinate service delivery for businesses whose core work remains physical.
Tokmak contrasts a reusable product platform with a roll-up model and argues that robotics is not a near-term substitute in highly varied service environments.
The founder framework emphasizes craftsmanship, agency, urgency, and patience rather than only technical capability.
The discussion presents private equity adoption of AI as a shift toward testing measurable return on investment, while Tokmak identifies education as a personally important future application.

AI in Real-World Services: The Hard Part Is Operations, Not Conversation

Source Audio / Video

The service problem is connecting judgment to dispatch

Netic founder Melisa Tokmak does not describe the product as simply an AI that answers calls. She says the system sits between a business and its customer, understands a need, applies operational rules, and then determines who should deliver service, when, and how. In HVAC, plumbing, and similar businesses, urgency, equipment, available technicians, and customer value can change a dispatch decision.

Tokmak says more than 70 percent of Netic customers are AI-first and that the customer's first interaction is handled by a Netic agent. That is the guest's company metric, not independently verified in the episode. It nevertheless defines the product direction: not only handling overflow calls, but operating at the first customer entry point.

A platform boundary is not a model boundary

Tokmak did not choose an acquisition-and-optimization roll-up. She says products in that model usually serve the acquired company, while she wants one product layer that many real-world businesses can use, leaving each business to focus on labor and service quality.

She likewise does not see robotics or frontier labs as direct near-term replacements. Variation in buildings, equipment, and human situations makes physical service difficult to standardize, while models still need harnesses, orchestration, software, and product work to complete the last mile. This is her judgment about the industry's timeline and competitive boundary, not a verified forecast.

Long-lived products need long-lived commitment

Tokmak uses a quote attributed to Martin Luther about a shoemaker to discuss craft: the point is not the symbol, but making the best shoe. She applies that principle to product work, which she describes as solving a problem for people one genuinely cares about.

Her hiring standard extends the same idea. She looks not only for one conspicuous act of initiative, but for a person who has started, sustained, and finished something over time. Her five-year vision is for Netic to manage the operational layer of service businesses while people continue to deliver the physical work; the company therefore also needs people willing to stay with hard work.

Enterprise AI is ultimately bought on observable value

Tokmak rejects the premise that essential-service industries are slow technology buyers. She says large enterprises are focused on value and gives an example of a roughly $500,000 contract closing in 14 days. This is a guest-supplied case, not independent verification of the transaction.

On private equity, she argues that the discussion should move beyond demos and cost cutting to whether results persist throughout the year and produce net-new revenue. She says Netic has generated more than $600 million for customers, also a company statement. She closes by naming education as an important positive AI application: technology can widen access, though action remains a human choice.