Why raising millions is not the real measure of success

When Min-Kyu Jung left his role as a corporate lawyer, the problem was straightforward. Contract review, a core part of legal work, was slow, manual, and repetitive. Teams were spending hours on tasks that required precision but little creativity.

“I was frustrated with a lot of the manual processes I went through as a lawyer and decided I could solve some of them through technology,” he says.

That frustration became Ivo, an AI platform designed to help in-house legal teams review contracts faster and with greater accuracy. The software analyses agreements, identifies risks, and suggests revisions, reducing review time by up to 75 percent. Its clients now include Uber, IBM, Shopify, Atlassian, Canva and Reddit.

The timing mattered. Advances in large language models made it possible to automate parts of legal work that had previously resisted change, particularly for manual processes like contract review and red-lining.

“It soon became clear that large language models were going to change the world in a big way.”

Since launching in 2021, Ivo has raised US$77 million in funding and scaled rapidly into global markets. But Jung is clear that capital is not the point.

Fundraising, he says, is often misunderstood.

“Fundraising is incredibly distracting, and you should try to spend as little time doing it as possible.”

The real driver of success is how well the business performs. Founders who spend too long raising money risk slowing the very progress investors are looking for.

Instead, Jung’s focus has been on building a product that solves a real problem. That requires holding two perspectives at once. Close enough to understand users better than they understand themselves, but far enough to form a view of how the industry should change.

“You need to have the ability to both zoom in and zoom out.”

That balance has shaped Ivo’s approach. Rather than treating AI as a generic tool, the company has focused on context. Many systems, Jung argues, behave like “a smart junior lawyer who joined your company five minutes ago and has amnesia”, lacking understanding of how a business actually operates. Ivo’s edge is in building that context into its product.

The path to this point has not been linear. Jung first encountered entrepreneurship as a student at Waipapa Taumata Rau, University of Auckland, taking part in the Velocity programme between 2016 and 2018.

“I heard about the Velocity $100K challenge, and it sounded like a lot of fun. I figured I didn’t have much to lose to fill out an application with my friend.”

That low-stakes entry point mattered. It provided early exposure to building ideas and testing them in a structured environment, without the pressure of immediate outcomes.

A more significant shift came later, when Jung began thinking beyond New Zealand. After connecting with investor Daniel Gross online, his sense of scale changed.

“One thing I appreciate about the Bay Area is that people are completely unapologetic about being incredibly ambitious.”

His advice to founders is direct.

“Don’t allow your geographic circumstances to dictate the scope of your ambition.”

Ivo did not sign its first New Zealand customer until after raising its Series A, reflecting a deliberate decision to build for global markets from the outset.

That decision also required trade-offs. The company relocated to San Francisco to access talent and operate at the centre of the AI ecosystem. Jung describes the benefit as proximity to both people and ideas, particularly in a fast-moving field where context changes quickly.

For early-stage founders, his lessons are practical. Keep fundraising tight and time-bound. Build something people genuinely need. Stay close to users but maintain a clear view of where the industry is heading.

Above all, do not confuse signals of progress. Raising capital can follow from building a strong business, but it does not define it.

Looking ahead, Ivo is continuing to expand its product and global presence, with new offices planned in New York and London. The company is also moving into adjacent use cases, helping not just legal teams but broader business functions extract insight from contracts.

For Jung, the underlying question remains the same as when he started. What work should still be done by humans, and what should not?