How One Manager’s Frustration with Endless Repetition Built Tines

If there’s one thing that can haunt technical practitioners, it’s the never ending cycle of repetitive tasks. Every day brings the same routine: checking alerts, handling phishing emails, onboarding or offboarding employees, or pulling system logs. These jobs are vital, but they are manual, time consuming, and endlessly repetitive, leaving little room for more impactful work.

Before AI took off, professionals dealing with these challenges wished for tools to handle their daily tasks. But since there was nothing like that in the market, the search often felt even more draining than the work itself.

This pushed Eoin Hinchy, who initially had no interest in becoming an entrepreneur, to pivot and build Tines, a company designed to solve that pain point for mission critical teams.

Tines – How One Struggle Sparked a Game Changing Idea

Eoin Hinchy never set out to be an entrepreneur. For most of his career, he was a cybersecurity practitioner working in technical roles at companies like eBay, PayPal, and DocuSign. He enjoyed the work, led strong teams, and had no grand ambitions of starting a business.

“I’m a first-time founder, a first-time entrepreneur, and honestly never had any grand ambitions of founding a company or building a business,” he said.

As he delved deeper into his role, a frustrating reality began to surface. As the company grew, so did the flood of repetitive work. Day after day, his team found themselves chasing phishing emails, clearing alerts, and repeating the same tasks they had already done that morning. For a leader, it was painful to watch: top talent stuck in a loop of monotony, losing energy and focus.

“You’ll be familiar with the kind of stuff: chasing down phishing emails, responding to alerts, or doing threat hunting. When we benchmarked it, we found that about 80% of my team’s time was spent doing something they had already done that day,” Eoin explained.

He added, “As a people manager, that’s not what you want for your team—it leads to human error, churn, lack of motivation, and frankly, it’s the reason we invented computers in the first place: so people wouldn’t have to do the same monotonous work over and over again.”

The problem wasn’t with his team’s skills—they were outstanding practitioners. But they weren’t software engineers, and writing the kind of sophisticated code needed to automate their workload was outside their scope.

In 2017, he set aside budget to find a proper tool. The goal was simple: give his team the ability to automate repetitive tasks without writing code. Over six weeks, they evaluated nearly a dozen platforms, from industry giants like Cisco and Microsoft, to independent SOAR tools such as Demisto, Phantom, and Siemplify, and even consumer automation apps like Zapier and IFTTT.

But the search was disappointing. Every tool came with major flaws—they were too complex, too limited, or priced in ways that made them impractical for real-world use. After weeks of frustration, he finally reached a breaking point and thought, “I think I can do a better job of this myself.”

This is why Eoin Hinchy and his cofounder Thomas Kinsella established Tines in 2018 with a mission to empower technical teams, especially those outside traditional software engineering roles, to automate the repetitive manual parts of their work without writing code.

“I founded Tines, with a North Star that was no more grandiose than building the product I wished I’d had as a practitioner,” Eoin recalled.

A Solution that Built from a Practitioner’s Perspective

Eoin Hinchy succeeded with Tines because he built the solution from a practitioner’s perspective, not just as someone chasing a business idea. He had spent over 15 years in cybersecurity, living the day-to-day pain of manual, repetitive workflows. So when he created Tines, he deeply understood the real-world problems, the variability between teams, and the limitations of existing tools.

According to him, many founders see security teams doing repetitive tasks and assume it’s easy to build a product to automate them. But unless you’ve actually worked in security, you won’t understand how wildly different each team’s workflows are.

“If you’re an entrepreneur or a founder and you look at this market like, ‘Oh man, security teams need a way to automate these dozen use cases, I’m just going to build a product that will allow them to do that and watch the cash roll in,’—well, unless you’ve actually been a security practitioner, it’s really hard to understand. The way Company A does phishing can be wildly different to how Company B does phishing, which can be wildly different to how Company C does phishing,” he articulated.

If the founders weren’t security practitioners, their products often tried to solve too many things at once—phishing, SIEM alerts, threat intelligence—without fully understanding the nuances of each use case. The result was tools that were too generic to be flexible, yet too specific to scale.

SOAR platforms were often marketed as all-in-one solutions where security teams could manage everything. But in reality, this promise has been made for decades and rarely delivers. Teams are too different, and their needs too varied, for one tool to do everything well.

Instead of trying to be everything, Tines focused on doing one thing extremely well: workflow automation. They didn’t try to replace tools like Jira, Slack, or threat intelligence platforms. They built a flexible automation layer that works with those tools, letting security teams automate their unique workflows without forcing them into rigid templates or interfaces.

“What we did that was unique to Tines was we built a very general automation platform, and we didn’t try to do the analyst collaboration, we didn’t try to do the case management, we didn’t try to do the threat intelligence. We just built a world-class workflow automation product initially,” he explained.

Eoin continued, “We said: you’ve already got Jira, you’ve already got Recorded Future, you’ve already got Slack. What you need is workflow automation. We’re not going to try and sell you a single pane of glass or a silver bullet. Maybe we’ll add some of these new SKUs as we get there, but the problem you have today is workflow automation—and that’s what we’re going to solve for you.”

How Tines Found the Perfect Blend Between AI and Workflows?

One thing about Tines is they made their establishment before the bloom of AI. Before that, the company built a good enough product that could be deployed in customers’ systems, but there were certain problems that were best suited for AI to solve.

However, Eoin was skeptical about AI at first!

“When LLMs first began to enter the public consciousness, like a little over two years ago now I guess, I was so skeptical. Like I was just like nah this isn’t going to work, like you know I’ve seen vendors promise AI for 20 years, like this is going to be trash. And I kind of discounted it a little bit,” he recalled.

“But then you know, as soon as I got my hands on the product, and as soon as a company began to explore it, we pretty quickly realized oh no hang on this is different, right. This is going to be the single most important technology change of the decade,” he added.

Tines didn’t want to just bolt on AI as a gimmick. Instead, they spent a year figuring out how to integrate it in a way that was genuinely useful for customers, not just for marketing purposes or to please investors.

The key was putting security and privacy first. Customers wanted to use LLMs, but they needed strict safeguards. Tines built infrastructure that let customers use AI securely — without exposing sensitive data, adding new subprocessors, or sending information off for fine-tuning and training.

Once that foundation was set, they could roll out practical features. For example, they introduced natural language data transformations, letting users describe what they wanted instead of writing complex rules. They also launched the AI Action, which allowed customers to drop an AI decision-making step into any workflow, such as detecting email scams or scanning code for vulnerabilities.

Because of this security-first approach, adoption was unusually high. Within months, two-thirds of their customers were using AI features — a rare feat in the enterprise AI space.

Still, customers pointed out two major problems with LLMs. First, the models don’t have access to real-time or proprietary data, and fine-tuning them is slow and expensive. Second, they can’t reliably take autonomous action, since their outputs are non-deterministic and unpredictable.

Luckily, Eoin found out that workflows were the answer to both issues.

“And so we fairly quickly realized well wow gez, like workflows is the perfect answer to both these problems, right. Workflows essentially give you real time access to any tool. And we’ve spent seven years building tens of thousands of Integrations that allow you to connect to any system, any data source, in any environment — Cloud, hybrid, on Prem — in real time,” he said.

He continued, “And so we were like okay well that’s workflows, it’s an answer to that problem. And then the problem around taking action and non-determinism, well hell, you know workflows are a great answer to that as well. Because I can predict exactly how this workflow is going to perform. I can decide what credentials it’s going to use, who should have access to it, how it should run, what happens if there’s an error, etc.”

At first, workflows were just considered a useful tool in a company’s tech stack. But Tines has seen them evolve into something much bigger — they’re now becoming the core element of enterprise technology strategy for the next 3–5 years.

Why? Because workflows solve the biggest problem with LLMs: how to actually get practical, reliable value from them in real business settings.

By acting as the “glue” that connects AI models with existing enterprise systems, workflows make it possible for companies to use LLMs securely, predictably, and at scale. That shift has driven rapid growth for Tines, since customers are increasingly relying on workflows to unlock real-world AI use cases.

Embrace Feedback and Requests from Customers!

Tines grew by staying open to customer feedback, even when it challenged their original assumptions.

“The mission has always been the same, but the way we thought we would get there has evolved enormously based on customer feedback and insight. A lot of the instincts we held true in those early days, our customers convinced us weren’t correct for various reasons,” Eoin said.

In the early days, Tines had a very clear idea of who their ideal customer was—cloud-native, high-growth software companies. That was the world the founders knew best, and naturally, they built their initial product for that audience.

But something interesting started happening over time: the people who loved Tines at those software companies would switch jobs and move into completely different industries, like banking, finance, manufacturing, or chemicals. And when they did, they wanted to bring Tines with them.

This forced the founders into conversations with companies that looked nothing like their original customer base. These companies often had stricter requirements—things like governance, compliance, and hosting—that Tines hadn’t initially built for.

Instead of pushing back, Tines leaned into these requests. They followed a simple rule of thumb: if a customer is willing to pay for a feature, build it.

The founder said, “One of the rules we had—it’s not really a rule, more like a mode of operation—is that we almost always build things the customer asks us to build. And that’s kind of contradictory to a lot of advice you’ll hear as a startup founder. Often, you’re told: don’t go too big too soon, don’t build weird features just for one company because they’ll be the only ones who use it. I think that advice is trash.”

He further explained, “Honestly. If a customer wants you to build something and they’re willing to pay for it—build it. If you’ve got a good enough engineering team and strong product instincts, you can build that feature in such a way that it’s not just for them—it’s applicable to 200 other companies that look and feel just like them.”

Tines Has Entered Its Growth Phase

According to Eoin, a disruptive and scalable product rests on several pillars: it must be exceptionally flexible to handle diverse use cases, easy to use for both technical and non-technical users, and reliable, secure, and trustworthy in high-stakes environments.

It should have universal applicability, connecting across workflows without creating silos, and be proven in critical real-world settings to demonstrate its value.

Tines has achieved all of the above, and now, they are in their growth phase.

Since its founding in 2018, Tines has raised a total of $272 million across six funding rounds, culminating in a $125 million Series C led by Goldman Sachs, SoftBank Vision Fund, and Activant Capital. With a current valuation of $1.125 billion, Tines has officially entered unicorn territory.

Early investors like Accel, Blossom Capital, and CrowdStrike helped fuel its momentum, recognizing the platform’s unique ability to empower technical teams to automate without writing code.

Tines serves a wide range of enterprise clients, particularly in security-conscious industries such as finance, healthcare, and pharmaceuticals. Its customers include global leaders like CrowdStrike and large pharmaceutical firms that use Tines for fraud detection and phishing response.

The platform integrates seamlessly with tools like Jira, Slack, and Recorded Future, allowing teams to build powerful, secure workflows across cloud, hybrid, and on-prem environments.