This video is an interview about how 25-year-old Max Junestrand, who had zero experience in the legal field, has successfully led Legora — a $675 million legal AI startup. Legora grew its team from 10 to 100 in just 13 months and raised $80 million, disrupting the conservative legal market. In this interview, Max shares deep insights on how to successfully build a vertical AI company, strategies for selling products to skeptical markets, and what the future of legal technology looks like.

1. Legora's Beginnings and the Transformation of the Legal AI Market

Legora is revolutionizing how legal work is done by building an AI-powered workspace for lawyers. Their service covers every area of legal work including review, drafting, and research. The existing legal software market was fragmented, and AI wasn't good enough for unstructured text or legal document work. But the arrival of GPT-3.5 changed everything.

Max explains that as soon as GPT-3.5 was released, he quickly built a prototype using the API available to developers and has since grown it into an enterprise-grade system used daily by tens of thousands of lawyers. He says he drew inspiration from a co-founder friend who spent four months at a large law firm over the summer summarizing trial cases. Initially, the founders — who had no legal background — built a tool that explained stock option agreements, but they quickly shifted focus to building a comprehensive system that every legal professional would want to use daily.

"When GPT 3.5 came out, everything completely changed. So we quickly built a prototype, and now we've scaled it to an enterprise-grade system serving tens of thousands of lawyers daily."

They put significant effort into complying with European data processing regulations, hosting all data within Europe, not using it for training, and maintaining no retention periods — meeting strict standards.

2. The Arrival of GPT and Legal Professionals' "Aha Moment"

Max recalls that before GPT-3.5, he attempted AI-based legal research, but Google's BERT model at the time was passable for English but terrible for Swedish. However, GPT-3.5 was a game changer. Max says his personal 'aha moment' was when he first used ChatGPT — conversing with a computer and having it respond felt like science fiction.

When Legora was introduced to the largest law firm in the Nordics, the managing partner had previously made critical remarks that AI was "more artificial than intelligent." But after seeing Legora perfectly answer queries about Swedish law, that lawyer experienced a genuine 'aha moment.'

Legora's true value was particularly demonstrated in due diligence processes, which require reviewing countless documents. Max describes scanning hundreds of employment contracts and asking, "Do all of these contracts contain an IP clause protecting the company's intellectual property?" Legora answered "yes, yes, no, no, yes, yes, yes" — accurately and always attaching citations. "This is revolutionary!" he felt.

"This is revolutionary. It reduces tasks that took days or hours down to minutes."

He adds that in the past, like the days of physical data rooms decades ago, corporate due diligence was very expensive, but now AI has nearly commoditized it, making clients unwilling to pay high fees for simple contract review.

3. Legora's Software Architecture and Innovative Features

Legora's software consists of two main parts: a web application and a Microsoft Word plugin.

Web Application Key Features

1. AI Agent: Initially a simple document chat feature, it has evolved into an agent capable of solving complex step-by-step workflows using in-app endpoints and external tools. For example, when a user requests a memo, the agent conducts research, converts the findings into the firm's standard language, writes a report, and delivers the final output.
2. Tabular Review: A feature Max calls 'the grid' — you input multiple files and multiple queries, and the system cross-analyzes them to produce results. The core scaling technology runs hundreds of thousands of queries simultaneously, ensures all citations are accurate, and efficiently finds relevant information within long documents. It's designed to account for legal document characteristics like always including definitions and cross-reference clauses.

Microsoft Word Plugin Innovation

Since lawyers primarily write and review contracts in Word, Legora focused on integrating AI directly into the Word environment. The Word plugin is like a 'Cursor for lawyers.' They approached it creatively, designing within the limited right-column space as if building a mobile app.

1. AI Assistant: This assistant not only reads documents but can also directly edit them. For example, you can request it to renegotiate a Master Service Agreement (MSA) for the buyer using a specific internal checklist or playbook.
2. Playbook Feature: Since LLMs alone aren't yet sufficient for negotiation, Legora implemented this through 'playbooks' — collections of rules containing approval/disapproval rules for specific clauses, example language, and fallbacks if the counterparty doesn't accept certain definitions. Users open a document, run a playbook, and the system reviews the contract, flags non-compliant sections, and suggests appropriate language.

This playbook feature extends beyond legal teams to other departments. All of Legora's sales representatives use Legora to negotiate NDAs before sending them to the legal team. This not only increases speed and accuracy but also improves quality and consistency, as playbooks created by the legal team become the standard.

4. Legal AI Innovation: Making the Impossible Possible

Max gives specific examples of how Legora has enabled legal work that was impossible just a few years ago.

• Handling diverse language: Early ML models were very vulnerable to legal language, especially when expressions varied between documents. For example, if a change-of-control clause was expressed differently across documents, it was hard to accurately grasp the meaning. But thanks to LLMs, Legora can now accurately identify meaning regardless of linguistic expression and extract needed information from large-scale contracts and documents.
• Cross-document comparison and editing: Redlining — comparing and editing hundreds or thousands of documents and playbooks within Word — was previously completely impossible.
• In-depth research: Gathering and deeply investigating hundreds or thousands of court decisions as well as laws and regulations in one place was hard to imagine in the past. With AI lowering information search costs, more queries can be made, and it's now possible to simultaneously search your own documents, the web, and case law and legal materials to write memos. Tasks that were previously unthinkable due to time or cost constraints are now possible.

"Redlining was previously completely impossible."

5. $80 Million Fundraise and Hypergrowth

Legora recently announced raising $80 million (approximately 110 billion KRW) in a Series B round led by Iconic and General Catalyst, with participation from Y Combinator, Benchmark, Redpoint, and others.

Legora was a team of about 10 when they completed YC, but grew rapidly to 100 in just 13 months. Max says that after confirming market demand for the product, he concluded: "We need to do more of this. We need to do it everywhere simultaneously." The combination of law and LLMs showed such obvious potential for success that they moved fast to become the 'winner' amid many competing legal AI startups.

Initially, onboarding customers required significant effort and first impressions were critical, so they paused sales for 4-5 months to focus on stability and scalability. Only after building a system that could comfortably onboard 1,000 lawyers per day did they begin scaling in earnest.

"We put the product on the market, and when law firms started buying after a single demo, we thought 'we're onto something.'" "We worked really hard on stability and scalability. Only after we had a system that could comfortably onboard 1,000 lawyers in a day did we accelerate."

They then rapidly expanded across Europe and into the U.S. market, establishing hubs in New York, London, and Stockholm, and placing local staff in Spain, France, and Germany. Max says he drove this hypergrowth with the spirit of "Everything, everywhere, all at once, right now."

6. Cracking the Conservative Legal Market

Other legal software companies funded by YC found selling to law firms the most difficult challenge. Most ended up selling to general corporations rather than law firms. But the situation changed dramatically about two years ago.

Max explains that Legora approached law firms with a 'we win, you win' approach. A significant portion of legal work is low-differentiation (e.g., due diligence), and when the service balance shifts, clients quickly adopt new approaches. Clients face price pressure, legal fees are very high, and they want efficiency.

Similar to when lawyers adopted computers, AI is now becoming an essential tool. Law firms believe that doing their best for clients generates more revenue long-term and is most important for maintaining brand reputation and trust. Many firms therefore want to be first movers in AI adoption or at least fast followers.

"We win, you win. We told law firms that they would need to adopt this technology one way or another, and we wanted to be that long-term partner — aligning our incentives with theirs." "Clients are facing price pressure. They want to be effective. Legal fees are very high. So when this balance breaks, you're almost forced to adopt AI."

When AI handles simple repetitive tasks to save time and money, lawyers can focus on higher-value work like complex M&A advisory. Max emphasizes that AI doesn't simply lead to a 'race to the bottom' but rather provides opportunities to perform more high-value work through efficiency.

Convincing AI Skeptics and Creative Use Cases

Persuading skeptical law firms was a challenge, but Legora has been supporting lawyers in remarkable ways.

• Mock trials through role-play: One lawyer had Legora role-play as opposing counsel and practiced arguing against it to win their case.
• Real-time courtroom use: A lawyer in Spain brought Legora into the courtroom, input all of the opposing party's evidence and documents, and queried in real-time as the opposing lawyer spoke — immediately identifying inaccuracies and countering them. He described Legora as "another suit of armor" in very poetic terms.

7. Starting Without Legal Expertise: Interviewing 100 Lawyers

Max openly admits that when they started Legora, none of the co-founders had any legal expertise. But they approached with deep humility about not knowing the industry.

"At this point I've become a hobby lawyer. But the way we approached it was by being extremely humble about the fact that we didn't know the industry."

They formed relationships with early partners built on daily feedback exchanges, collaborating with the philosophy: "We don't know exactly where the future is going, and neither do you. So let's work together so that whatever happens, we all come out as winners." They now employ many lawyers who communicate directly with product teams and customers.

Max advises founders looking to build vertical AI software in other fields (logistics, insurance, finance, etc.) not that "you don't need domain expertise" but rather to "learn the domain expertise." He personally interviewed 100 lawyers during the early startup phase.

He used LinkedIn to propose lunch meetings to lawyers, offering to pay their hourly rate, but no one charged — they happily agreed to meet. Max says that being "someone people want to help" has been tremendously useful in his career, and calls it a very underrated skill.

"I interviewed 100 lawyers. I texted them to have lunch with me and said I'd pay their hourly rate, but no one did." "One of the traits that has been very useful in my career is that I'm someone people want to help. I think that's a very underrated skill."

During interviews, he says it took time to understand that work methods differ by position and department. He also advises actively engaging lawyers by offering ideas from your technical background, making them want to give advice.

8. Competing Against Existing Legal Tech Giants

The legal tech market has long had large incumbent players that grew through massive M&A. They were often unpopular with end users but held entry barriers (data moats) from vast data and large contracts.

But AI has completely changed the game. Software development costs have dropped sharply, new categories are being created, and many existing point solutions are rapidly becoming irrelevant. Max emphasizes Legora's ability to outperform teams of thousands of engineers with just 30 people.

"AI has really changed the rules of the game in terms of how quickly you can ship something." "It's remarkable that we can produce results much faster with just 30 people than teams with thousands of engineers."

Legora was 10 people when graduating YC, now 100, moving at much higher speed than incumbents. The 'data advantages' and 'long-term contracts' held by large companies are no longer strong lock-in effects. Buyers don't want 5-year contracts because the world is changing too fast — they prefer 1-2 year terms.

Law firms are now moving beyond the 'experimentation phase' of 2023 and 2024, carefully evaluating which technology to adopt long-term. They're looking not just at the technology itself but at the "rate of change." Firms want to work with partners who will lead them from point A to point B, whether that means increasing revenue through AI-first strategies or streamlining operations to improve profitability.

9. Technology Stack and Model Strategy

Legora was built on Azure from the start since that's what most of their customers primarily use. Initially, only OpenAI's GPT models could be served through Azure, but now they flexibly use diverse models including AWS, Claude, Gemini, GPT, and Mistral.

The most important technical strategy was "building everything so that models can be hot-swapped at any time." This ensures the entire system improves whenever a model improves. Additionally, for cost efficiency, they use classification models to serve simple models for simple queries and complex models for complex queries.

"The most important thing was building everything so that models can be hot-swapped at any time." "If you ask a simple query, you get a simple model; if you ask a complex query, you get a complex model. This is partly to lower margins, but sometimes you only need a water gun and don't need a bazooka."

10. AI Buyers Within Law Firms: Innovation Departments and Partners

Who buys and uses AI within law firms varies somewhat depending on the firm's size.

• Large law firms:
  • Innovation departments: Large firms often have innovation departments that decide on software purchases and drive overall innovation. Max says he gets the most energy from collaborating with them. They focus on improving efficiency but are often not the direct users.
  • Innovation practitioners: Innovation practitioners working in specific groups like M&A or dispute resolution collaborate with their teams to build use cases with tools like Legora and improve staff technical capabilities.
  • Billing targets: Lawyers at large firms must meet billable hour targets, so they tend to stick with methods that took 6 hours. Innovation teams have the important mission of changing these practices and introducing more efficient methods.
• Small and mid-size firms: Without innovation departments, partners make purchasing decisions directly.

Sales Success Strategy in a Conservative Industry

When selling in a conservative industry, there's pressure to "convince everyone," but Max advises: "Start small."

"You have to convince everyone. Or you start small."

First, work with one partner and their team to make them a 'rockstar.' Then other partners think "What are they doing? That looks amazing, we want that too" — and expansion happens naturally.

However, he emphasizes that a bottom-up approach is impossible in the legal industry. Individuals can't procure software, and the purchase process involves procurement teams, IT teams, security reviews, data privacy reviews, and many other steps. Selling to senior people first is therefore crucial.

11. Max's Background: From Esports to Startups

Before co-founding Legora at 23, Max had accumulated diverse experiences. At 18, he had to decide between becoming a professional Dota 2 player or going to university.

"When I was 18 and it was time to apply for university, I actually had two options. Become a pro Dota 2 player, or go to university."

Max says that even if he won the top Dota 2 tournament and earned $10 million, the question "what next?" lingered. University, on the other hand, would open up greater possibilities like what he's doing now.

He 'hacked' Sweden's university system where engineering and business are separated by attending two universities simultaneously. During the COVID-19 pandemic, with online lectures, he attended classes on two laptops simultaneously and even took exams that way.

During university, he worked as a programmer building statistical models for esports betting. He then interned at Norhen in Stockholm, where he encountered other entrepreneurs whose 5-year plan was "to conquer the Nordics" — making him feel that their ambitions were different and bigger than his own. He gained experience at McKinsey, BAMLO, and startups like Depict, which he recalls as a 'talent magnet' company that produced remarkable people.

12. Hypergrowth: From 10 to 100 in 13 Months

After completing YC, Legora achieved explosive growth from 10 to 100 people. Max says this growth was about more than just adding headcount — it was about learning to delegate. Even for things he knew well, doing everything himself wasn't scalable, so hiring people far better than him in specific areas and delegating to them was critical.

Legora notably hired many former founders. Max mentions that one of the 'secret playbooks' followed by successful YC companies is hiring former founders.

"We've scaled the team with a lot of entrepreneurs. Not just the skills we're looking for, but also the way we've built the company. Because we effectively run multiple companies within the company." "One of the sort of secret playbooks of YC companies, some of the best ones, is that the first people you want to hire are all former founders."

Former founders bring ownership mentality and proactive attitudes to problem-solving, which was perfectly suited to Legora's organizational style of 'running multiple companies within a company.' Max also says they hired experienced people who had gone through the growth from 100 to 500 to prepare for scale-up.

Company Culture and Ideal Talent

Max emphasizes that a company's early culture is shaped by the people founders hire. Whenever Legora establishes a new hub, they dispatch the most capable employees from the Stockholm office to set the new hub's culture.

Legora looks for creative people who discover and solve problems and take on more responsibility beyond simply performing their assigned tasks.

"In many of my interviews, I often ask 'What have you done beyond your role at the company?' Here I look for creativity, the ability to find and solve problems, and taking responsibility for more than just your assigned work."

Legora prefers generalists who can use AI to accomplish 10x more, even in departments like marketing. Where 30 people were once needed for a marketing team, they can now operate with 5 — seeking outstanding and ambitious talent. Max says these traits are increasingly important in an era where tools provide enormous leverage.

13. The Future of Lawyers: AI Agent Managers

Max provides intriguing insights into how a lawyer's daily life might change in 5-10 years. He predicts that lawyers will increasingly transition to a role of "reviewing and managing work rather than directly performing it."

Lawyers will now need to manage the balance between client expectations and the work performed by AI agents. The role will be to direct AI agents, supervise their work, confirm the output is accurate and meets standards, and manage how those deliverables are presented to clients.

"I think lawyers are increasingly entering a workspace where they review work rather than actually perform it, and they'll be managing client expectations and the work of AI agents." "You're effectively directing them, watching them perform the work, making sure everything they do is accurate and meets your standards, and managing how that work is delivered to the client."

Ultimately, lawyers with domain expertise will be essential for delivering final work product, but because AI is advancing so rapidly, it's difficult to precisely predict 5-10 years out, he adds.

14. When You Feel Product-Market Fit (PMF)

Max describes Product-Market Fit (PMF) as "a sensation of seemingly infinite demand — feeling like you're being pulled by the market."

"That feeling is best summarized as an almost infinite demand — a sense of being pulled by the market."

This emerges when the product works properly and moves beyond mere 'experimental AI' to become a 'tool essential for core work.' If the system goes down, calls come in immediately saying "I can't work because of this" — that's how critical it's become.

In the early days, many partners believed in Legora's potential and joined 'the journey,' but now Legora has taken them from point A to point B, and they believe it will continue to grow.

15. Why They Stayed in Stockholm: Targeting Europe, Not SF

Y Combinator generally advises startups to move to San Francisco, but Legora decided to stay in Stockholm. Max explains:

• Market competition: The U.S. market is far more competitive, which can force companies to narrow their focus.
• European expansion strategy: Legora targeted the broad European market from the start, becoming the best in Nordic countries like Finland, Denmark, and Norway before expanding to Spain, France, Germany, London, and then the U.S. They've already entered 15 markets and mastered the expansion method.

"The reason we stayed in Stockholm is that we needed a market to grow in. Going to the U.S. not only means more competition, but it tends to make the company focus on a narrower area." "We quickly realized we were the best in Finland, in Denmark, in Norway. And then we expanded to Spain, France, Germany, London, and the U.S."

Becoming the big fish in a small pond first, then entering the larger American pond, proved to be an effective strategy.

16. Toward Category Leadership in Legal AI

Legora raised $80 million in mid-May 2025, opened a New York office, and has established partnerships with prominent U.S. law firms, positioning itself as a global category leader in legal AI. Max is confident they're already leading in multiple respects.

He notes that rather than being satisfied with solving problems, new problems are constantly emerging. The deeper they go into the legal software stack, the more they find that "the boundary between software and services is blurring."

"We're finding that the boundary between software and services is blurring."

Because AI is advancing so rapidly, Legora must evolve at the same pace. Ultimately, the category leader in this field must go beyond simply building software to serve as a strategic partner for major law firms, helping them win in the AI transition. To this end, Legora has rapidly scaled its workforce while maintaining culture, urgency, and speed.

17. Advice for Vertical AI Company Founders

Max shares several important pieces of advice for founders looking to build vertical AI companies.

1. Don't get locked into an AI provider: Avoid becoming dependent on a specific model provider, and don't try to directly compete with AI research labs. AI labs advance rapidly, making competition impossible.
2. Clearly identify your value creation point: Understand clearly where you're adding value and building a long-term moat. Legora builds products like a 'boat' so that when the tide rises, everything gets better — maximizing leverage.
3. Find a narrow category: Initially, find narrow categories that AI models can't reach or where models can be used in very creative ways.
4. Understand domain-specific language: Taking AI scribing as an example, general AI scribing isn't easy — in specific domains like healthcare or law, much customized prompting and methodology is needed to use the right terminology. Models shouldn't just output the most likely answer; they need to write the way a lawyer drafts a clause.

18. What It Means to Work at Legora: Ambition and High Expectations

For people considering joining Legora, Max highlights the following:

• Ambition and problem-solving drive: Legora seeks people with the ambition and will to answer "We have a huge problem and a huge mountain. How do we climb it?"
• High expectations: Legora is not a traditional Swedish 9-to-5 work environment. There are good aspects like Fika (Swedish coffee break culture), but the passion and expectations are much higher. This is because they pursue personal growth, entrepreneurial growth, and leadership growth.
• Rigorous hiring process:
  • Sales/Go-to-Market team: Candidates must pitch the Legora product themselves.
  • Engineering team: Candidates must build a Legora prototype, leveraging AI-generated code while being able to explain it and design scalable systems.
• Global talent attraction: While Stockholm is a small ecosystem, Legora is attracting talent from across Europe — Madrid, Amsterdam, Germany, Paris — to Stockholm. Together with other great companies, they're turning Stockholm into an 'AI hub.'

Conclusion

The story of Max Junestrand and Legora demonstrates that even without legal domain experience, you can successfully transform a conservative market through innovative ideas, execution, and a customer-centric approach. By building an organizational culture that constantly learns, delegates, and grows at the pace of AI's rapid advancement, and by emphasizing their role as strategic partners for legal professionals in a new era where the boundary between software and services is blurring, Legora's trajectory continues to inspire high expectations.