Meet Ronen Korman, Co-Founder & CEO at Dataflow Management Platform: Metrolink.ai

Metrolink is a platform that tackles the challenges any data project has to face very early on, at the phase of data integration. This stage may not be as important as extracting value from this data, from a strategist’s bird-eye viewpoint, but it is a necessary precondition for everything else in the workflow. And what we have persistently noted is that while data availability is skyrocketing, and BI, ML, and other data-related fields are making colossal strides forward, integration is lagging behind—by a lot. This gap ends up torpedoing the larger data transformation process, preventing companies from updating their business models for the Big Data era.

What are the main obstacles here? We have identified a few. First, there simply aren’t enough data engineers to take care of the surging data needs of businesses. Second, the fact that data integrations are often done in a coding-heavy manner makes it hard for businesses to quickly respond to changing patterns and business questions. This results in performance slumps and lower operational agility.

Furthermore, data is growing more complex: Companies often need to tackle hundreds of streaming and event-based data flows, incorporating all of them into a sophisticated structure before even beginning to make sense of the data flowing in. This also makes it harder for businesses to scale up, both when it comes to their data infrastructure and larger business operations, as their real capabilities lag behind their own needs.

Metrolink was built to solve all of these issues. It’s not just another ETL tool, the idea behind it is bigger and more ambitious. Our platform allows data teams to address the shortage of data engineers by scrapping the need for coding as part of the integration, which also slashes the length of the data-to-value cycle. Metrolink also allows more team members to function as data experts by equipping them with a user-friendly and versatile tool for all data-related tasks.

This no-code approach, together with the advantages of a scalable high-performance backend that can cope with data complexity, brings a unique combination of performance, speed, and value. With Metrolink, companies can handle their data integrations within hours through a step-by-step no-coding design UI that is just as functional as the coding-based approach.

The platform allows analysts to do all the engineering they need themselves, and fast, making the entire team more versatile and dynamic. It also gives data engineers the freedom to focus on more complex and important tasks, such as developing new building blocks for analysts to use on the platform. Metrolink automatically scales data pipelines up and down based on their performance and helps companies lower maintenance costs and fix bugs on the go, while also giving them ongoing monitoring and analytics capabilities.

How did you come up with the idea for the company?

Throughout my 30 years of service in the Israel Defense Forces and the Israeli Security Agency, I was focused on developing their data capabilities. We developed amazing tools and executed mind-blowing operations to get access to the most relevant data and expose the darkest secrets of our adversaries.

At a certain point, having held more senior positions, I understood that getting data was not the problem anymore. I saw two separate cases where we had all the raw data we needed, but we failed to process it fast enough, failed to connect the dots in time. It was up to us to flag these threats for Israel’s national security, but we didn’t issue the alerts we should have sent out. This led me to realize that we are not adaptive enough. Today, the data at hand and the questions we need to answer with it are changing on the go, and we can’t adjust our data integration infrastructure fast enough to keep up. We processed data fast, lightning-fast, but that was legacy data, which has already lost its relevance.

At first, I thought this was just the problem with being a “big governmental cooperation.” After a long and thorough review, though, I understood that the same problems are alive and kicking in the commercial world.

Palantir was a model of reference, but instead of following their GTM strategy, we believe that organizations should have the flexibility to solve their challenges with their own talent. And we are giving them the power to do so! Also, it is important for us to make our product as affordable as possible price-wise and design it in a way that keeps users’ data unexposed to third-party companies, including ourselves.

How has the company evolved during the pandemic?

Covid only emphasized how right we were. While governments and health organizations are generally familiar with using data, the questions and challenges they faced changed rapidly, sometimes twice a day, and they struggled a lot with adapting to the unraveling crisis. The analysts at the state and organization level knew what the question was and understood the data that could give them the answer, but by the time they could get their hands on an actionable dataset, it was already too late. We all know how this went down. There were many setbacks, many mistakes, and many third-party companies contracted to outfit the analysts with the solutions they needed got their hands on troves of sensitive personal data.

As to our company’s everyday life, we decided to work in line with two principles. First of all, we decided that “when in doubt, don’t doubt.” We push our team to act with personal responsibility and stay at home if they suspect they may have been infected, but don’t know for sure yet. Secondly, we believe that office life is important: Together, we work and brainstorm more effectively, and team building and spirit are even more important. At the same time, though, we were mindful of the risks and other factors, even the time team members spend on their daily commutes. So the model we ended up following was this: We spend three days together in the office, then work the rest of the week from home.

When Omicron was in full swing, we decided to work full-time from home, mainly because we did not want the whole team to catch the disease at once. In general, my advice to companies navigating the pandemic is to be adaptive and walk the talk, not just talk the talk!

What can we hope to see from Metrolink in the future?

We will transform the data world the same way Apple and Google turned regular cell phones into what they are today. We will be the operating system for data that serves as a mediation platform between data and value.