ChatGPT vs. Harvey, Legora, BEAMON: what’s the difference?

Anyone looking into AI tools for legal work today soon comes up against a fundamental question: what sets ChatGPT apart from specialised legal AI tools such as Harvey, Legora or BEAMON, and does that difference really matter day to day?

The answer doesn’t lie in individual features. It lies in a fundamental architectural decision: horizontal AI versus vertical AI. This difference explains why the same language model can be helpful in one context and a serious professional risk in another.

Horizontal AI: powerful, but not tailored to any specific industry

ChatGPT is the best-known example of horizontal AI. Horizontal tools are designed to help as many people as possible with as many tasks as possible. They write emails, explain code, draft marketing copy, and draft legal clauses. This versatility is their greatest strength. And their structural problem.

A horizontal tool isn’t tailored to any specific industry. It doesn’t know legal databases, a law firm’s internal document collections or professional regulatory requirements. It produces linguistically convincing text without knowing whether the content is correct. In a legal context, that’s not an abstract risk.

In its order of 29 April 2025 (ref. 5 U 1/25), the Higher Regional Court (OLG) of Celle found that a lawyer had cited four decisions from various higher regional courts that couldn’t be found in a single legal database. Shortly afterwards, the Local Court (Amtsgericht) of Cologne reached a similar finding (ref. 312 F 130/25): every source in a brief had been made up. In both cases the courts assumed the citations were AI-generated; which tool was actually used has not been established. What matters is this: the tool itself gave no indication that the cited judgments didn’t exist.

Vertical AI: built from the ground up for one field

Tools like Harvey, Legora and BEAMON take a fundamentally different approach. They’re built from the ground up for legal work, not just in the user interface but across their entire architecture. BEAMON shows this particularly clearly:

• Source verification: answers are grounded in verified legal sources. BEAMON checks statutory citations and case law references against connected legal databases instead of generating them freely
• Automatic source references: every statement is linked to its source. One click takes you straight to the underlying legal source, instead of having to trust the output blindly
• Data protection and professional secrecy: BEAMON is certified to ISO 27001:2022 and SOC 2 Type II and fully complies with the German Federal Lawyers’ Act (BRAO) and § 203 of the German Criminal Code (StGB). Client data stays in the EU/EEA and isn’t used for AI training
• Word Plug-in: BEAMON can be embedded directly in Microsoft Word. Contract review, redlining and comments happen where the lawyer already works, with no copying between tools
• Traceability: every answer includes verifiable source references. The lawyer sees not just the result but also where it comes from, and can check it independently

What separates vertical legal AI tools from ChatGPT isn’t a single feature. It’s how these qualities work together, and the fact that they’re part of the design from the start, not added afterwards. If you’d like to see what that looks like in practice, you can try BEAMON for free: ai.bryter.io/sign-up.

Why this matters in practice

The difference between horizontal and vertical AI becomes particularly clear in three areas of everyday legal work.

First: hallucination risk. ChatGPT produces plausible text without distinguishing whether a legal source exists or not. Specialised legal AI tools reduce this risk structurally, because answers are checked against real databases. That doesn’t eliminate hallucinations completely, but it makes them identifiable and controllable.

Second: confidentiality. Entering client information into a horizontal tool puts you in a legal grey area, or takes you beyond it. Specialised legal AI tools are designed from the start to handle sensitive legal data. BRAO, § 203 StGB, GDPR: these requirements are built into the architecture, not bolted on afterwards.

Third: workflow integration. ChatGPT delivers text. A specialised legal AI tool delivers structured output that flows straight into the next step: into the redline, into the extraction table, into the Word document. That doesn’t just save time. It reduces errors at handover points.

What ChatGPT can still do

Horizontal AI has its place, including in everyday legal work. For non-confidential, exploratory tasks, ChatGPT is a useful tool: structuring first drafts, explaining legal terms, organising thoughts, generating checklists. It’s easy to get started with, and for simple tasks the results are often usable.

The problem starts where these boundaries aren’t clearly drawn. If you use ChatGPT as a research tool for case law, enter client information, or put AI-generated output into briefs without checking it, you’re leaving the territory the tool was made for.

Asking the right question

The question isn’t: ChatGPT or legal AI? The question is: for which task, with which data, and with what responsibility?

If you want to structure a thought or sketch out a first draft, you can work with ChatGPT. If you’re carrying out contract reviews, leading due diligence, processing client data or producing output that has to stand up legally, you need a tool built for exactly that.

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