Laurel Secures $100M for AI Time Intelligence, Transforms Legal Tech
Eight years after its initial introduction at Mishcon de Reya’s MDR Lab, legal technology firm Laurel has achieved significant growth, recently securing a $100 million Series C funding round. The company, which is now profitable, is expanding its product capabilities. Artificial Lawyer recently spoke with co-founder and CEO Ryan Alshak to discuss Laurel’s journey, its milestones, challenges, and future direction.
The genesis of Laurel stemmed from a deeply personal frustration experienced by Alshak during his time as a litigator at a major law firm. He recounted the "dehumanizing" process of meticulously accounting for every six-minute increment of his day, often relying on memory, spreadsheets, and email searches to reconstruct his weekly activities. This inefficiency, he noted, was widespread, leading to billions of dollars in lost or delayed revenue across professional services due to professionals' inability to accurately recall their work. This challenge prompted a fundamental question: "What if machines reminded us what we did at work, instead of the other way around? What if we could use AI to surface time for lawyers, accountants, and consultants alike?" This question became the foundation for Laurel, evolving from a timekeeping solution into what Alshak describes as a "Time Intelligence layer for knowledge work."
Over the past eight years, the market perception of timekeeping software has undergone a significant transformation. Initially viewed merely as a cost center, timekeeping is now recognized as a strategic asset. Alshak explained that accurate time data forms the bedrock for critical business functions such as pricing, profitability analysis, staffing, forecasting, and ultimately, a coherent AI strategy. Concurrent with this shift, the advent of generative AI has reshaped expectations of what technology can achieve. While automated timesheets are rapidly becoming standard, the true evolution lies in not only capturing work but also explaining it, analyzing it, and guiding strategic decisions based on that data.
One of the most impactful lessons learned on this journey, according to Alshak, is that "time is not just a billing input. It’s the most under-utilized strategic asset in professional services." This realization profoundly altered Laurel's approach. Traditional billable hours, he argues, offer only a partial view of a professional's contribution. Non-billable activities—such as business development, recruiting, and training—are crucial drivers of culture, innovation, and long-term value, yet they often remain unmanaged because they are unseen. Laurel addresses this by surfacing what it calls 'True Time,' providing a complete picture of where time is actually allocated.
The greatest challenge for Laurel has been convincing the industry that timekeeping could be fundamentally improved—not just automated, but made accurate, trustworthy, and actionable. Alshak acknowledged the "scar tissue from legacy tools" that bred skepticism. Overcoming this required a dedicated, pilot-by-pilot approach. However, once firms witnessed Laurel's effectiveness, observing that it saved professionals 1-2 hours per week while increasing revenue by an average of 7.26%, adoption accelerated. This success, driven by word-of-mouth in an industry where trust is paramount, fueled Laurel's growth.
By 2025, Laurel has established itself as a significant player in legal tech. The company now powers time management for many of the world's leading professional service firms, including top-tier consulting firms (MBB), the Big-4 accounting firms, and the AmLaw 5 law firms. Annually, Laurel processes over $4.4 billion in professional time. The company boasts a net revenue retention rate exceeding 175% and is cash-flow positive. With its recent Series C funding, Laurel is now making substantial investments in AI and data products, transitioning its focus from mere time capture to comprehensive time intelligence.
Laurel's product roadmap is guided by a three-stage vision:
- Account: To transform timesheets from a creation task into a finalization process for professionals.
- Understand: To leverage AI to explain the captured time, detailing what was done, for whom, and its significance.
- Automate: To quantify and identify low-leverage workflows that can be automated by intelligent agents, thereby enabling professionals to focus on higher-value tasks.
Alshak confirmed that Laurel has successfully "nailed" the "Account" stage and is now deeply immersed in the "Understand" phase. Looking ahead to 2026, the "Automate" stage will take center stage. This involves developing advanced analytics for fixed-fee pricing, capacity forecasting, measuring the impact of generative AI, and providing firm leadership with unprecedented visibility into the deployment of both time and talent.
Addressing the perennial question of whether time-based billing in law firms will ever change, Alshak asserted that it is "already changing." He pointed to increasing client demands for predictability and the transformative impact of AI on the nature of work. The traditional incentives of time-based billing—where more hours equate to more revenue—do not align with a future where machines can draft a significant portion of legal documents. Drawing on Charlie Munger's wisdom, "Show me the incentive, and I’ll show you the behaviour," Alshak emphasized that for the legal profession to embrace AI at scale, it must rethink its pricing models. This, he concluded, is only feasible with a clear understanding of the cost of delivery. While time-based billing may not always dominate, Alshak firmly believes that time data will always be critical, and Laurel aims to be the platform that maximizes its value.