100,000 Processes: How Tomato AI Designed for Viral Adoption Inside Enterprise Accounts

100,000 Processes: How Tomato AI Designed for Viral Adoption Inside Enterprise Accounts

Enterprise software typically follows a predictable pattern: land in one department, deliver value, then spend months convincing other departments to adopt. Expansion requires sales cycles, budget approvals, and executive sponsorship for each new team.

In a recent episode of Category Visionaries, Ofer Ronen, CEO and Co-founder of Tomato AI, explained how his team engineered a different expansion model. Today, Tomato AI manages “more than 100,000 live processes” across enterprise customers—not through coordinated rollouts, but through organic viral spread.

The secret wasn’t just product-market fit. It was deliberate architectural decisions that made sharing, adapting, and expanding inevitable.

The Use Case Diversity Foundation

Most enterprise software companies fight to narrow their positioning. Pick one department, one use case, one value proposition. Tomato AI made the opposite bet.

“Orchestration is one of these things that can be applied in so many different ways across your organization,” Ofer explains. This wasn’t a positioning problem to solve—it was the foundation of their viral growth strategy.

Procurement uses Tomato AI for vendor onboarding. Legal uses it for contract approvals. Finance orchestrates quote-to-cash. IT routes support tickets. Sales ops manages deal workflows. Each team has completely different processes, yet all run on the same platform.

This diversity became the viral mechanism. When someone in procurement builds a vendor workflow, their colleague in legal doesn’t think “that’s not relevant to me.” They think “if procurement can orchestrate their processes, I can orchestrate mine.”

The product architecture had to support this. “We built the product to be completely self-service,” Ofer notes. Users needed the ability to “connect it to all the different systems that they have, build a process, launch it into production” without involving other teams.

Ownership as Viral Design

Traditional enterprise software centralizes control. IT owns the platform, configures access, and manages deployments. This prevents chaos but kills viral spread—nobody can adopt without IT approval.

Tomato AI inverted this model with a critical insight: “These processes belong to the business teams. They’re not IT-owned processes.”

This wasn’t just philosophy. It shaped fundamental product decisions. Business teams needed the ability to create their own workflows, connect their own systems, and deploy their own processes—all within security guardrails set by IT.

The architecture separated concerns elegantly. IT configured organizational security policies, approved system integrations, and set governance boundaries. Within those boundaries, business teams had complete autonomy.

This created the perfect viral conditions. When a procurement manager builds a successful workflow, their colleague doesn’t need to submit a request to IT, wait for approval, and schedule an implementation. They just build their own workflow.

The friction between seeing value and replicating it dropped to near zero.

The Self-Service Adaptation Model

Viral spread requires more than visibility—it requires easy adaptation. Seeing someone else’s success is inspiring, but only if you can replicate it for your own needs.

Most enterprise platforms fail here. Workflows are custom-built by implementation teams, documented inadequately, and too complex to adapt without expertise. Seeing a colleague’s solution doesn’t help if you can’t modify it yourself.

Tomato AI’s self-service architecture solved this. When someone sees a workflow that partially fits their needs, they can clone it, modify the logic, adjust the integrations, and deploy their version—all without involving the original creator or an implementation team.

This adaptation pattern accelerated viral growth exponentially. One procurement workflow becomes templates for vendor onboarding, contract renewals, and purchase approvals. Each adaptation spawns new adaptations. Within months, procurement has dozens of processes, each optimized for specific scenarios.

Then someone from legal sees procurement’s success and adapts their vendor workflow into a contract approval process. Finance sees legal’s process and adapts it for invoice approvals. The viral spread isn’t linear—it’s networked.

Security That Enables Rather Than Blocks

Viral adoption in enterprises hits a predictable wall: security review. The first team adopts, loves it, shares it widely—then IT security shuts it down pending formal evaluation.

Tomato AI designed to prevent this blocker. “We actually have more enterprise-grade security than Workato, than Zapier, than any of these other guys,” Ofer states. SOC 2 Type 2 compliance, comprehensive data governance, enterprise access controls—all built in from the start.

This meant the first team to adopt Tomato AI could pass security review immediately. By the time other teams started using it, the security approval was already complete. IT didn’t need to re-evaluate for each department.

More importantly, the security architecture supported multi-team usage without creating coordination overhead. Each team’s processes ran independently, within their own security boundaries, without affecting other teams. Legal’s workflows couldn’t access procurement’s data unless explicitly configured. Finance couldn’t modify IT’s processes.

This isolation enabled teams to adopt and expand independently, without creating security concerns that would trigger centralized control and slow viral spread.

The AI Acceleration

As AI capabilities improved, Tomato AI added a feature that supercharged viral adoption: natural language process creation.

Previously, adapting a workflow required understanding the original logic and manually reconfiguring it. With AI, users could describe modifications in plain language. “Someone can just describe what they want to do” and Tomato AI would handle the technical implementation.

This eliminated the last barrier to viral spread. Someone with zero technical expertise could see a colleague’s procurement workflow and say “build me something similar but for legal contracts, with different approval chains and compliance checks.” The AI understood the intent and built the adapted process.

The viral velocity this enabled was dramatic. Processes that previously took days to adapt could be replicated in minutes. Teams that previously needed training to build workflows could describe them conversationally.

The Metrics That Matter

Traditional enterprise software measures accounts, seats, and annual contract value. Tomato AI tracks something different: live processes.

“More than 100,000 live processes” running across their customer base represents genuine viral adoption. Each process is someone solving a real problem. Each cluster of processes is a team orchestrating their complete workflow. Each company with hundreds of processes is viral spread across departments.

This metric reveals the expansion model’s power. If Tomato AI grew through traditional enterprise sales—landing accounts, then slowly expanding—they might have large contracts but relatively few processes per customer. Instead, they have organic usage spread that creates deep product dependency.

When a company runs hundreds of processes on Tomato AI across multiple departments, switching costs aren’t just contractual—they’re operational. Those processes represent real work being done. Replacing Tomato AI means rebuilding all of them.

The Bottoms-Up Enterprise Model Realized

“We actually believe that in order for us to be successful, we need to have a bottoms up approach,” Ofer explains. But bottoms-up usually means starting small and hoping to expand. Tomato AI engineered bottoms-up to guarantee expansion.

The product architecture—self-service creation, use case flexibility, team ownership, security isolation, and AI-powered adaptation—wasn’t just about ease of use. Each decision amplified viral potential.

Self-service removed adoption friction. Use case flexibility ensured relevance across teams. Team ownership enabled independent expansion. Security isolation prevented coordination overhead. AI acceleration eliminated technical barriers.

Together, these decisions created a viral coefficient inside enterprise accounts. Each successful process increased the probability that someone would build another. Each team using Tomato AI increased the likelihood another team would adopt.

Designing for Inevitable Expansion

Most enterprise software hopes for expansion. Tomato AI designed for it.

The difference shows in outcomes. Traditional enterprise platforms might expand from one department to three over 18 months through coordinated sales efforts. Tomato AI expands from one team to a dozen organically, driven by users solving their own problems and sharing their solutions.

For B2B founders building horizontal platforms, Ofer’s approach offers a framework: viral growth inside enterprises isn’t about making your product shareable. It’s about making it independently valuable to each team, easily adaptable to their specific needs, and free from coordination overhead.

When those conditions align, expansion becomes inevitable. Users don’t adopt because sales tells them to—they adopt because their colleague showed them something useful and they can replicate it themselves in minutes.

That’s how you get to 100,000 processes. Not through top-down rollouts, but through bottom-up inevitability.