Episode 15: Ari Zilka

Most companies are drowning in data. They monitor everything, store everything, and pay millions to track what is happening across their systems. But monitoring alone does not solve the real problem.

In this episode of The Disruptors, Ari Zilka explains how MyDecisive AI is shifting the conversation from collecting data to making decisions in real time.

Ari Zilka has spent his career solving hard infrastructure problems.

From the early days of Walmart.com to high-speed data systems, big data, enterprise operations, and observability, Ari has repeatedly been brought into complex environments where scale, speed, reliability, and decision-making matter. He describes himself as a “clutch player,” someone companies call when they need to solve difficult technical problems under pressure.

That background led him to MyDecisive AI.

The episode begins with a broader conversation about artificial intelligence. While much of the public discussion focuses on consumer-facing AI tools, Ari focuses on the enterprise backbone: the systems, data streams, infrastructure, monitoring tools, and operational decisions that keep modern businesses running.

For Ari, the core issue is that companies are spending enormous amounts of money on monitoring, but not getting enough value from it.

In enterprise technology, monitoring is often referred to as observability. Companies pay to collect massive volumes of telemetry data about how their systems are performing. This data can show whether servers are responding, applications are slowing down, releases are causing problems, or infrastructure needs to scale.

But the traditional model has a flaw: companies collect and store huge amounts of data, then rely on people to interpret it later.

Ari explains that most monitoring platforms were built around “data at rest.” In other words, the data is collected, stored in databases, and queried after the fact. That can be useful for asking why something happened in the past, but it is less effective when the business needs to know what to do right now.

MyDecisive AI is built around a different idea: the most important operational decisions should happen while data is still moving.

Ari describes this as a streaming problem rather than a storage problem. Instead of only storing monitoring data and looking back later, MyDecisive AI aims to sit in the flow of data and help companies decide what action to take in real time. Should the system scale up? Should it scale down? Should a service restart? Should a release roll back? Should traffic fail over to a disaster recovery environment?

Today, many of those decisions are still made manually.

That is where Ari sees the opportunity for AI.

He argues that humans may make a handful of operational decisions from monitoring data in a day, while an AI-driven decision framework can potentially make thousands. The point is not just to reduce cost. It is to move from passive observation to active operational intelligence.

The conversation also explores Ari’s time at Walmart.com. He describes being responsible for scale during a period when the company was trying to grow its online business. At one point, leadership wanted to double revenue again, but Ari identified a deeper problem: the site’s conversion rate was too low. The traffic challenge was not only about infrastructure capacity. It was about business efficiency, customer experience, and whether the company was asking the right questions from its data.

That lesson carries directly into MyDecisive AI.

Ari believes many companies are stuck in cycles where teams build, measure, rebuild, undo, and repeat without truly understanding what actions are creating value. Monitoring data should help businesses make better decisions, but when it is treated only as stored information, it becomes expensive and underused.

The episode also touches on the venture capital environment for AI companies. Ari explains that while AI startups can attract interest, companies solving deeper infrastructure problems often face a harder road because the work requires real technical execution, customer education, and a shift in how enterprises think.

For Ari, that is exactly why the opportunity matters.

MyDecisive AI is not trying to add another dashboard to the enterprise stack. It is trying to change the way companies act on operational data.

What makes this episode relevant

This episode explains one of the least visible but most important challenges in enterprise AI.

The public often experiences AI as a chatbot, a writing tool, a search assistant, or a content generator. But inside large companies, AI has a different kind of potential: helping businesses make faster, better, and more automated operational decisions.

That is the problem Ari Zilka is focused on.

Companies already collect massive amounts of monitoring data. They know when systems are slow, when servers are strained, when users abandon flows, and when releases create problems. But knowing something happened is not the same as knowing what to do next.

That gap is where MyDecisive AI is positioned.

Ari’s argument is that enterprise monitoring needs to evolve from a passive system of observation into an active system of decision-making. Instead of paying only to collect and store more data, companies need systems that can act while the data is still in motion.

For CEOs, CTOs, infrastructure leaders, DevOps teams, and investors, this conversation is especially relevant because it shows where AI may create value beyond the obvious consumer use cases. The next wave of AI adoption will not only be about better prompts or better models. It will also be about whether companies can use AI to operate faster, reduce waste, improve reliability, and make decisions at machine speed.

The episode also matters for entrepreneurs because Ari’s story shows the reality of building in a deep infrastructure category. The opportunity is large, but the work is not easy. It requires technical credibility, customer education, patient capital, and the ability to explain a complex problem in a way the market can understand.

Watch the full episode to understand how Ari Zilka is building MyDecisive AI, why observability is ready for disruption, and how real-time decision-making could change the way enterprise systems operate.