Vertical AI Startup: Legal AI Harvey

In recent years, the evolution of generative AI has been remarkable, expanding the potential for efficiency across all professional fields. The legal industry is no exception. Harvey, which we are introducing here, has developed a domain-specific AI platform that supports legal and professional service operations and has already been adopted by Fortune 500 companies, major law firms, and accounting firms. In this article, based on statements and case studies from Winston Weinberg, CEO and co-founder of Harvey, we will explain why the company is growing significantly in the legal tech sector and how it is leveraging Vertical AI.

1. Background and Origins of Harvey

1-1. Encounter with GPT-3

Harvey was born when co-founder Gabe showed GPT-3 to Weinberg. He began to explore "how much of the complex legal work I was doing could be automated using GPT-3." At the time, GPT-3 was not yet widely known, but Weinberg, sensing its potential, said he was surprised that "this model could be used to draft specific legal documents and prepare for legal consultations."

1-2. Experiment on Reddit's "r/legaladvice"

One of the first experiments they conducted was to have GPT-3 answer about 100 "landlord-tenant dispute" questions from Reddit's r/legaladvice (a community where posts seeking legal advice are gathered) by combining them with "Chain of Thought" prompts. As a result, they obtained quality so high that many lawyers vouched that "this answer could actually be sent to a client." This was the first step toward the birth of Harvey.

2. Building an AI Platform Specialized for Legal Work

2-1. Focusing on the "Massive Amount of Grunt Work" in the Legal Profession

As a former lawyer, Weinberg felt that "early in a lawyer's career, there is a lot of repetitive document review and research work, and strategic discussions with clients are limited." These tasks require a large number of personnel at law firms and generate high costs. Also, for young lawyers, there was a dilemma where routine tasks were prioritized over honing true expertise.

2-2. Aiming for an End-to-End Workflow

Harvey is not just a "text generation AI," but is characterized by its ability to support multi-stage legal workflows from end to end, such as "large-scale document analysis," "coordination with external data," "creation of checklists for each requirement," "automatic generation of document drafts," and "visualization of the review process."
For example, they are aiming for a flow where, when a set of documents accompanying an M&A is uploaded, the AI automatically determines the appropriate competition law filings for the country or region and drafts and proposes the necessary documents. Weinberg expressed his expectation that "in the near future, AI will significantly automate the creation of S-4s (filing documents with the U.S. Securities and Exchange Commission)."

3. How to Conquer a "Conservative Industry"

3-1. Adoption by Major Corporations and Large Law Firms

Harvey has emphasized collaboration with large law firms and accounting firms (Big Four) since its inception. While most startups often start with transactions between small and medium-sized enterprises or other startups, Harvey viewed "collaboration with world-renowned top-tier firms as the shortcut to gaining trust."
For example, major law firms with histories ranging from several decades to over 100 years, such as Arnold & Porter and Allen & Overy, conducted pilot tests of Harvey, and because the results were highly evaluated, adoption has spread to other firms and companies.

3-2. Addressing Conservatism and Reliability

The legal field is a strict industry where "mistakes are not allowed." There is also deep-rooted anxiety about automation. Harvey has developed features that ensure human lawyers can always review output results, as well as mechanisms to clearly state "which documents or provisions were referenced to reach this conclusion." This creates an environment where partner lawyers who bear final responsibility can use it with peace of mind.

4. Expansion Beyond the Legal Domain

4-1. To Other Professional Services such as Tax and Audit

Harvey is expanding its business not only to the legal field but also to other professional services such as tax, audit, and consulting. This is because the "process of reviewing vast amounts of documents according to rules and regulations and creating application documents as necessary" is very similar.
For example, "legal due diligence," "tax due diligence," and "financial due diligence" in an acquisition all ultimately require handling a large amount of document review and verification of rule compliance. By repurposing and expanding the legal-related AI system that Harvey has already built, efficiency can be achieved in these services as well.

4-2. Balancing Advanced Specialized AI with Cross-Functional Tools

The company adopts an approach that simultaneously pursues "expansion" (segmentation into specific domains) and "aggregation" (simplification of the final user experience). The strategy is to develop advanced workflows specialized for certain fields (e.g., M&A due diligence) and combine them so that they can ultimately be used through "a single, simple UI."

5. Product Strategy and Organizational Building

5-1. Domain Knowledge + Engineering + AI Research

To build highly practical systems in the complex legal domain, Harvey actively hires "senior-level lawyers" to evaluate models and conduct user interviews. Furthermore, they have established a system where engineers who are well-versed in the latest AI research and Large Language Models (LLMs) can quickly incorporate new features. The key to their success lies in a trinity of development: staff who understand the "mechanisms of large law firms," researchers who know "cutting-edge AI," and engineers who "build products with a focus on speed."

5-2. Talent Development and a Culture of "Ownership"

At Harvey, which has expanded rapidly in just two and a half years, there are many cases where young members serve as managers, and both inside and outside the company, people are surprised by their growth. Weinberg emphasizes that they "value agency and ownership more than experience in a specific field." He also says that the sense of speed in making immediate improvements without fear of failure, and the "dedication to victory, like constantly chanting '
Job’s not finished' (Job’s not finished) and chanting it continuously," are the driving forces that keep them moving forward in the fast-paced AI industry.

6. Future Outlook and the Future of "Professional Work"

6-1. How Will the Role of Lawyers Change?

As work efficiency improves through AI, what will happen to the jobs of professionals such as lawyers and accountants? To this question, Harvey explains that "routine tasks will be significantly reduced, allowing more time to be spent on strategic advisory work." Young lawyers will be able to grow earlier without being tied down by document review, and partners will be able to focus on complex legal risks and communication with client companies.

6-2. The Expanding Potential of Vertically Integrated AI

Once a vertically specialized platform incorporates various rules and data and accumulates numerous workflows, it becomes easy to expand horizontally into other areas. In fact, just as Harvey is seamlessly expanding from law to tax and audit, comprehensive support that was difficult with traditional "one industry, one function" software is becoming a reality.

Harvey's case shows the potential for significant efficiency gains and new business models to emerge in industries requiring specialized knowledge by leveraging Large Language Models (LLMs). Moreover, it is beginning to shift to an advanced stage that goes beyond mere "document generation" to "automating multiple steps previously performed by humans through the coordination of AI agents." The success of
Harvey in the legal industry was born from the transformation of conservative culture, the challenge of complex regulations, and the technical ability to realize end-to-end workflows. In the future, similar vertically specialized AIs may rapidly develop in professional fields such as tax, audit, and even medicine and finance. The evolution from "mere text generation" to "actual business flow integration"—in this trend, the role of professionals will also change. Automating routine tasks so that humans can focus on high-level judgment, communication, and building trust with clients. Such a future is just around the corner.