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

Melisa Tokmak founded Netic, a company that builds AI agents to handle customer interactions and operational workflows for large essential service businesses. Netic positions itself between service companies and their customers, handling everything from initial customer contact (via voice, text, or web) to service dispatching and labor allocation. The platform uses AI to understand customer needs, assess technician capabilities and availability, consider customer lifetime value, and optimize service deployment—tasks traditionally requiring hundreds of support staff.

Tokmak explains that incumbent solutions rely heavily on human staff working in unpredictable conditions. Large service companies struggle with growth because they must continuously hire to scale, making margins difficult to maintain. Before Netic, these businesses operated with skeleton crews during off-hours, leading to missed customer opportunities during peak demand periods (heat waves, winter, etc.). Over 70% of Netic's customers are now "AI-first," meaning the customer's first interaction is with a Netic agent.

When asked why she built a platform rather than pursuing AI-enabled roll-ups (buying and optimizing multiple businesses), Tokmak cites three reasons: her personal mission to build for real-world businesses and the people in her hometown who work in these industries, her skill set as an engineer and product builder rather than an M&A specialist, and the vision that a horizontal platform can scale across many industries rather than being limited to specific acquired companies.

Tokmak emphasizes that these service industries are not technologically backward but rather pragmatic and value-focused. Closing a half-million-dollar contract can take only 14 days because decision-makers carefully validate ROI. She notes that companies were already trying to leverage satellite data, neighborhood analytics, and cross-selling opportunities across portfolios—Netic simply consolidates these efforts into one platform.

On hiring, Tokmak prioritizes agency—evidence of consistent initiative and follow-through across someone's life, not just professional accomplishments. She digs into life stories and asks what the hardest thing a candidate has ever done was, looking for patterns of sustained commitment rather than short-term wins. She warns against hiring people with a "permanent underclass mentality" who fear obsolescence in 18 months; instead, she seeks people willing to dedicate years to building something well.

Regarding competition from large AI labs like OpenAI, Anthropic, and Meta, Tokmak argues that while these labs excel at core model building, they lack focus on specific enterprise use cases and operational durability. Labs build products quickly and abandon them quickly, but enterprises need sustained, reliable systems. Moreover, enterprise AI success requires orchestration, harnesses, product design, and deep domain knowledge—not just superior models. She positions Netic as needing strength across three layers: models, orchestration/software, and product.

On private equity ownership of these businesses, Tokmak notes that the PE playbook has shifted from finding undervalued gems to actively creating value. Many PE firms are experimenting with AI but sometimes approach it like software, expecting week-one results. She advocates for showing tangible ROI through live deployments (Netic has generated over $600 million in customer revenue) rather than demos. The conversation with PE-owned companies increasingly focuses on net new revenue generation rather than cost-cutting alone.

Tokmak expresses excitement about AI's potential in education, where access to learning and feedback could remove geographical and socioeconomic barriers—reflecting her own experience gaining a Stanford scholarship from a small Turkish town. She also highlights the importance of shifting mainstream AI narratives from job displacement fears to positive human impact, using examples like helping people during emergencies or understanding health data.