7 Go-to-Market Lessons from Building a $100M Pipeline with Bottom-Up Enterprise Sales

7 Go-to-Market Lessons from Building a $100M Pipeline with Bottom-Up Enterprise Sales

In a recent episode of Category Visionaries, Ofer Ronen, CEO and Co-founder of Tomato AI, revealed how his team built a nine-figure pipeline by systematically rejecting traditional enterprise sales wisdom. Managing over 100,000 processes across enterprise customers, Tomato AI’s journey offers a masterclass in modern B2B go-to-market strategy.

Lesson 1: Self-Service Infrastructure Is Your Enterprise Moat

Most founders treat self-service and enterprise as mutually exclusive strategies. Ofer proved they’re complementary—if you build the right foundation.

“We built the product to be completely self-service,” Ofer explains. But this wasn’t about reducing costs or moving downmarket. It was about removing friction for sophisticated enterprise users who didn’t want to wait for implementation teams.

The critical insight: enterprise self-service requires enterprise-grade security from day one. Tomato AI invested heavily in SOC 2 Type 2 certification and data governance features early. “We actually have more enterprise-grade security than Workato, than Zapier, than any of these other guys,” Ofer notes.

This dual investment—self-service experience with enterprise security—created a unique competitive position. While competitors chose between SMB self-service or enterprise white-glove service, Tomato AI offered both simultaneously.

Lesson 2: Let Use Case Diversity Drive Bottoms-Up Adoption

Process orchestration presents a unique challenge: the applications are nearly infinite. For most companies, this would be a positioning nightmare. Ofer turned it into an advantage.

“Orchestration is one of these things that can be applied in so many different ways across your organization,” he explains. Rather than fighting this diversity, Tomato AI embraced it. They built a platform flexible enough that procurement, legal, finance, and operations teams could each solve completely different problems.

This approach works because it aligns incentives perfectly. When sales reps pitch broad platforms, they face skepticism. When an operations manager discovers they can solve their specific problem in minutes, adoption happens organically.

The lesson: if your product can serve multiple use cases, don’t force convergence through marketing. Build true flexibility and let users discover their own applications.

Lesson 3: Business Teams Own Their Processes—Build for That Reality

Traditional enterprise software assumes IT owns everything. Tomato AI bet on a different future.

“These processes belong to the business teams. They’re not IT-owned processes,” Ofer states. This philosophical stance shaped every product decision. Rather than requiring technical expertise or IT involvement, Tomato AI built tools that business users could operate independently.

This created natural viral growth within enterprises. A procurement manager builds a vendor onboarding workflow. A colleague in legal sees it working and builds their own contract approval process. IT gets involved only when needed—for security reviews or system integrations—not as gatekeepers.

The GTM implication: when business teams own the processes, they own the budget decisions too. This eliminates lengthy IT approval cycles and creates faster sales cycles, even in Fortune 500 companies.

Lesson 4: AI Timing Matters More Than You Think

Tomato AI raised their Series B “right around when ChatGPT launched.” This timing proved transformational, but not for obvious reasons.

“AI actually makes everything that we’re doing much, much easier and much better,” Ofer explains. The AI wave didn’t just add features—it fundamentally lowered adoption barriers. Previously, building workflows required technical skills. Now, “someone can just describe what they want to do” and Tomato AI’s AI builds it.

But here’s the deeper lesson: Ofer saw AI as a category accelerant, not just a product enhancement. “The way that people work is going to completely change,” he predicts. AI agents will execute tasks, and orchestration platforms will manage those agents.

For founders, this means thinking beyond “adding AI features.” Ask how AI trends will reshape your entire category, then position accordingly.

Lesson 5: High-Touch Support Doesn’t Mean Traditional Implementation

As Tomato AI scaled from 30 to over 100 employees, they faced pressure to adopt traditional enterprise service models. They resisted.

“We’re definitely more high touch than we used to be,” Ofer acknowledges, “but we still want to be much less high touch than these traditional vendors.” The distinction matters. Traditional vendors assign implementation teams that do the work for customers. Tomato AI provides experts who guide customers doing their own implementation.

This preserves the self-service DNA while addressing enterprise needs for support. It also creates better outcomes—when customers build their own processes, they understand them deeply and can modify them as needs change.

The lesson: scaling enterprise doesn’t require abandoning your original GTM motion. It requires evolving it intelligently.

Lesson 6: Category Creation Requires Practitioner-First Education

“We’re actually creating a new category,” Ofer explains. Process orchestration sits between workflow automation, integration platforms, and business process management—but differs from all three.

Most companies approach category creation through executive education—whitepapers, analyst relations, executive briefings. Tomato AI inverted this. They let practitioners experience the category through hands-on use.

When someone builds their first orchestrated process connecting multiple systems, they understand the category viscerally. They become advocates who can explain it to their executives better than any sales rep could.

This approach takes longer but creates more durable category understanding. Practitioners who’ve experienced the value firsthand become true believers, not just buyers checking a box.

Lesson 7: Bottoms-Up at Scale Requires Intentional Hybrid Design

The hardest GTM challenge Tomato AI faced wasn’t initial traction—it was maintaining bottoms-up principles while landing larger enterprises.

“We’re definitely going after larger organizations,” Ofer confirms. But this didn’t mean abandoning self-service. It meant building a hybrid model where self-service drives initial adoption and expansion, while sales teams facilitate strategic relationships.

This hybrid approach requires careful orchestration. Too much sales involvement kills the self-service motion. Too little leaves enterprise deals stalled at small-scale usage. Tomato AI threads this needle by letting product usage drive qualification, then deploying sales resources strategically.

The key metric: sales team involvement scales with customer potential, not customer size. A Fortune 500 company trying Tomato AI for one use case gets light-touch support. That same company orchestrating 50 processes gets strategic account management.

The Compounding Effect

These seven lessons compound. Self-service infrastructure enables bottoms-up adoption. Use case diversity drives viral spread within organizations. Business team ownership creates budget flexibility. AI timing accelerates adoption. High-touch support scales the model. Category creation builds moat. And hybrid design sustains it all at enterprise scale.

The result: “over $100 million in pipeline” and “more than 100,000 live processes” running on the platform. Not through traditional enterprise sales, but by building a go-to-market engine that works with how modern enterprises actually adopt software.

For B2B founders navigating similar horizontal platforms or category creation challenges, Ofer’s path offers validation: the bottoms-up enterprise model works. You just need to build it properly from the start.