Mage vs. Harvey: Purpose-Built M&A Diligence
Harvey is a powerful legal research assistant. Mage is purpose-built for M&A due diligence extraction. Different tools for different problems.
Request Demo| Feature | Mage | Harvey |
|---|---|---|
| Structured data room analysis | ||
| Automated document classification | ||
| Cross-document provision extraction | ||
| Tabular comparison grids | ||
| Batch processing (500+ docs) | ||
| Risk flagging and prioritization | ||
| Source-linked extractions | ||
| General legal research | ||
| Contract drafting assistance | ||
| Multi-practice area support |
Key Differentiators
Structured Output
Mage produces structured, tabular output organized by document and provision type. Every cell in the grid maps to a specific location in a specific document. This is fundamentally different from chat-based summaries or research answers.
Data Room Scale
Mage is built to process entire data rooms as a single unit. Upload 500 documents and receive a comprehensive extraction grid in minutes. The architecture handles the volume and complexity that M&A transactions demand.
Diligence Workflow
Mage is designed around the specific workflow of M&A diligence: upload, classify, extract, review, export. Every feature serves this workflow. There is no general chatbot interface because diligence requires structured analysis, not conversation.
When to Use Each Tool
Both tools serve legal professionals. The right choice depends on the task.
Use Mage When
- You need to analyze an entire data room
- You want structured extraction across hundreds of contracts
- You need cross-document provision comparison
- You need tabular output for diligence memos
- You need to identify change of control and consent requirements
Use Harvey When
- You need general legal research across topics
- You want drafting assistance for legal documents
- You need Q&A about individual documents
- You work across multiple practice areas
- You want a conversational AI interface for legal work
Frequently Asked Questions
Common questions about Mage vs. Harvey
Harvey is a general legal AI assistant designed for legal research, drafting, and Q&A across practice areas. Mage is purpose-built for M&A due diligence, focusing specifically on contract extraction, document classification, and structured analysis of data rooms. They solve different problems and can be complementary.
Harvey can answer questions about individual documents and assist with legal research. However, it is not designed for structured extraction across hundreds of contracts, cross-document comparison, or the tabular analysis workflows that M&A diligence requires. These are the specific capabilities Mage was built for.
For M&A contract review specifically, Mage provides purpose-built capabilities that a general legal AI does not: automated document classification, structured provision extraction across entire data rooms, cross-document comparison grids, and risk flagging. For general legal research and drafting, Harvey has broader capabilities.
Yes. Many firms use general legal AI tools for research and drafting alongside Mage for diligence-specific workflows. Mage handles the structured extraction and analysis of data room documents, while general AI tools support the broader legal work that surrounds transactions.
Mage is architected for batch processing of entire data rooms, handling hundreds or thousands of documents in a single workflow. The platform processes documents concurrently and presents results in a structured grid. General AI assistants typically work with individual documents or small sets.
Yes. Every Mage extraction links directly to the source paragraph in the original document. Attorneys can verify any finding with a single click. Unlike chat-based summaries, Mage provides structured, tabular output where every cell traces back to a specific document location.
It depends on the use case. For the core diligence workflow of analyzing data rooms, extracting provisions, and producing structured findings, Mage is purpose-built for that task. For broader legal research, memo drafting, and Q&A across practice areas, a general AI assistant may be more appropriate.
See Mage in Action
Request a demo to see how purpose-built diligence software compares to general AI tools on your actual documents.
Request Demo