Max Junestrand, CEO of Legora

Max Junestrand opens by recounting how Legora recruited actor Jude Law for their marketing campaign. After being initially rejected, the team spent six months pursuing Law, ultimately winning him over by showing genuine customer testimonials from lawyers describing meaningful life improvements. Law brought his own SNL scriptwriter and the cinematographer from Oppenheimer, producing a campaign that generated 17 touchpoints and even brought in leads through word-of-mouth.

Max then describes his background, noting he studied computer science and business, did a stint at McKinsey, and worked at two YC startups before co-founding Legora. He kept his McKinsey offer as a safety net until Legora was accepted into Y Combinator, at which point he declined the offer. He describes the YC experience as grueling — his entire team of ~10 moved into an Airbnb, doing sales calls from 1am–10am and then attending YC sessions, grinding constantly.

He describes his early sales approach in Stockholm as unusually energetic for legal tech — running around with a briefcase, projecting extreme enthusiasm, and leveraging social proof from established Nordic law firms to close deals. He made a tactical swap where the engineering team returned from YC to handle customers while he stayed to fundraise, pitching to firms like Benchmark. He recounts how Peter Fenton said 'the guy is perfect, the only problem is he's from Sweden' — a comment Max uses as fuel.

Max discusses Legora's long-term product strategy, noting that in October 2024 they had only 1M ARR while a competitor focused solely on tabular review had 50M ARR, yet Legora's bundled approach has since surpassed them. He emphasizes the importance of a longer-horizon strategy even in fast-moving markets.

As of the interview, Legora has grown from 40 people a year ago to nearly 500, operates globally, and has passed $100M ARR. Max is most excited about the post-Christmas step-change in model capabilities enabling proactive agentic workflows — for example, agents that autonomously structure M&A data rooms and run due diligence queries over 20–30 minutes. He compares Legora's trajectory to where AI coding tools are now, noting legal AI trails code AI by about six months.

Finally, Max addresses the 'what if OpenAI/Anthropic does this?' concern by drawing an analogy to MongoDB vs. AWS, arguing that the real question is what remains defensible as models improve. He points to proprietary data, workflow integration, user behavior, and enterprise trust as Legora's moats.