Table of Contents
The race to digitize the legal industry is no longer a theoretical debate about the future; it is a high-stakes sprint for market dominance. In a sector historically defined by slow-moving tradition, AI-native platforms are now scaling at a velocity that rivals the fastest-growing SaaS companies in history. Legora, a leading contender in this space, recently reported adding $7 million in Annual Recurring Revenue (ARR) in a single 24-hour period—a figure that exceeded their revenue for the previous two years combined.
Max Junestrand, co-founder and CEO of Legora, believes the legal tech landscape is rapidly evolving into a "winner-takes-all" market. While competitors like Harvey garnered early headlines, Junestrand argues that long-term victory belongs not to the first mover, but to the platform that delivers the superior product. From aggressive US expansion to a strategic pivot toward Anthropic’s models, Legora is betting big on becoming the centralized operating system for the legal world.
Key Takeaways
- Unprecedented Growth: Legora added $7M in ARR in a single day in late 2025, signaling a massive acceleration in enterprise adoption.
- The "Winner Takes All" Dynamic: Junestrand predicts the market leader will capture 90% of the value, leaving the remaining 10% to be shared among competitors.
- Model Promiscuity: Legora has shifted significantly from OpenAI to Anthropic (Claude) for enterprise workflows, citing superior reasoning capabilities.
- The "Application Layer" Thesis: Unlike competitors focusing on fine-tuning models, Legora invests in the application layer, betting that general models will continue to improve rapidly.
- Future of Law Firms: The industry faces imminent consolidation, where technology becomes the primary differentiator and billing models eventually shift from seat-based to consumption-based.
The Battle for Supremacy: Legora vs. Harvey
The narrative in Silicon Valley often suggests a geographic split in the legal AI market: Harvey winning the United States and Legora dominating Europe. Junestrand firmly rejects this dichotomy. While Legora began with strong roots in the Nordics, their aggressive expansion into the US has fundamentally shifted their revenue mix. As of 2025, the US has become Legora’s largest market by revenue.
This shift was driven by a strategic realization that European startups often fail in America by attempting to launch without sufficient enterprise validation. Legora’s approach was to secure top-tier US firms—such as Cleary Gottlieb and Goodwin Procter—while still operating from Europe. This proved their capability to handle high-stakes American legal work before they officially put boots on the ground in New York.
"It doesn't really matter who was first. It matters who's best. We are moving at such a rapid pace... Number one will grab 90%. And number two to number 10 will share the remaining 10%."
The speed of execution is critical. Legora grew its headcount from 30 to 300 in just 12 months. Junestrand attributes much of this velocity to the structural advantages of the US labor market, specifically the two-week notice period compared to Europe’s three-month standard. This allows for rapid scaling of talent that matches the company’s quarter-over-quarter revenue doubling.
Technical Strategy: The Shift to Anthropic and the "Application Layer"
One of the most distinct strategic divergences between Legora and its competitors is its approach to Large Language Models (LLMs). Early in the AI boom, many companies poured resources into fine-tuning models. Legora took a contrarian stance, believing that general foundational models would improve so quickly that fine-tuning was a waste of capital.
Betting on the Rising Tide
Junestrand likens this strategy to building boats rather than trying to control the ocean. By focusing on the application layer—the workflow, the user interface, and the legal-specific scaffolding—Legora ensures that as model capabilities rise (the tide), their product automatically improves without requiring expensive technical debt.
Why Anthropic is Winning the Enterprise
While Legora started as an OpenAI-exclusive shop, the company has pivoted heavily toward Anthropic’s Claude models. According to Junestrand, the shift wasn't just about raw power, but about the model’s ability to handle complex, multi-step instructions without feeling "lobotomized."
"We are pretty diehard Anthropic right now... Opus 4.5 feels like a VP. You give it [a task], here's the thing I want, go execute, and it just does it."
However, loyalty in the AI space is fleeting. Legora maintains a policy of "model promiscuity." If Google’s Gemini or a future iteration of GPT demonstrates superior performance for legal reasoning, the platform is architected to switch immediately. This flexibility allows them to offer clients the best possible outcome regardless of which tech giant currently holds the crown.
The Evolution of the Law Firm Model
The integration of generative AI is not just changing how lawyers work; it is poised to restructure the economics of law firms entirely. Junestrand predicts a wave of consolidation, where the "Am Law 200" potentially shrinks to an "Am Law 20." In this environment, technology is no longer a back-office support function but the primary lever for competitive differentiation.
From Billable Hours to Consumption Models
Currently, AI platforms largely rely on seat-based pricing (SaaS), a model that simplifies procurement for law firms. However, Junestrand argues this is a transitional phase. As AI agents begin to run tasks 24/7—creating a world where inference runs continuously even while lawyers sleep—pricing must inevitably shift to a consumption-based model.
This transition will likely align with a change in how law firms bill their clients. The traditional billable hour is under pressure. As AI reduces the time required for tasks like due diligence or contract review, firms will move toward fixed-fee arrangements for standard work, while reserving hourly billing for high-level strategic advisory.
The Impact on Junior Lawyers
A common fear is the elimination of junior legal roles. While Junestrand admits that the number of trainees needed to execute a transaction will decrease, he remains optimistic about labor demand. He draws a parallel to software engineering: despite tools making coding faster, the demand for engineers has increased because the volume of software being built has exploded.
Similarly, as the cost of legal transactions drops, the volume of legal work is expected to rise. The "pie" gets bigger, even if the labor required per slice decreases.
Scaling a "Missionary" Culture
Rapid hypergrowth presents a unique cultural challenge: maintaining the intensity of a startup while scaling to hundreds of employees. Legora’s philosophy centers on hiring "missionaries, not mercenaries"—individuals driven by the outcome of winning rather than just a paycheck.
To preserve this culture, the company emphasizes aggressive celebration of wins and transparent competition. Whether it is engineering teams competing to shave milliseconds off document upload times, or sales teams tracking deals on New Year's Eve, the goal is to create momentum where winning becomes a habit.
"There is no number two. There is only being number one. There's only winning. And everything else is losing."
This intensity was exemplified by a critical decision in mid-2024. Despite high demand, Junestrand and the board decided to freeze sales for six months to rebuild their infrastructure. They risked stalling growth to ensure the product could handle enterprise scale. When they reopened the doors in October, they were ready to onboard 1,000 lawyers a day, leading to their record-breaking revenue figures in December.
Conclusion
The legal AI sector is currently in a "land grab" phase, where speed, reliability, and strategic model selection are determining the future giants of the industry. Legora’s trajectory suggests that the market is moving away from point solutions and toward comprehensive platforms that serve as the central nervous system for legal work.
As law firms face pressure to consolidate and modernize, their choice of technology partner will likely dictate their survival. For Legora, the strategy is clear: remain model-agnostic, focus on the application layer, and run faster than the competition to secure the 90% market share reserved for the winner.
