Mage vs. Harvey
Mage is purpose-built for M&A due diligence with 200+ predefined clause types, disclosure schedules, and closing-ready deliverables. Harvey is a full-platform legal AI with research, drafting, and workflows across every practice area. Different tools built for different problems.
Request Demo| Feature | Mage | Harvey |
|---|---|---|
| Tabular extraction and review tables | ||
| Batch document processing (500+ docs) | ||
| Source-linked extractions with citations | ||
| Predefined M&A clause types and risk checks | ||
| Disclosure schedule automation | ||
| Variance detection across agreement sets | ||
| Amendment chain and document relationship detection | ||
| Closing checklists and deal-specific memos | ||
| 80+ language support | ||
| Legal research (LexisNexis, 500+ sources) | ||
| Contract drafting and Microsoft integrations | ||
| Litigation support and multi-practice coverage | ||
| Custom no-code workflow builder |
Ad-Hoc Extraction vs. M&A Intelligence
Harvey lets you build review tables from scratch. Mage comes with the M&A diligence workflow built in. The difference is between configuring a general tool and using a purpose-built platform.
Mage extracts 200+ M&A-specific clause types across 14 risk categories into a structured grid. Change of control, liability caps, termination rights, IP assignment, non-competes, and more. Each extraction is risk-scored and cited to the source text. Harvey can create review tables, but you define the questions from scratch each time. Mage has the M&A intelligence built in.
Every document is automatically classified across 50+ categories and linked to related documents. Mage detects amendment chains, identifies which provisions supersede earlier versions, and extracts the current effective terms. Harvey can store documents in Vault, but does not automatically classify them into legal categories or detect document relationships.
Mage covers the full lifecycle: data room ingestion, document classification, structured extraction, redline comparison, variance detection, disclosure schedules, closing checklists, and firm-branded memos. Harvey covers document Q&A and ad-hoc review tables. The M&A diligence workflow from classification through closing does not exist in Harvey.
What Sets Mage Apart
Predefined M&A Intelligence, Not Prompt Engineering
Harvey lets you create review tables by writing custom prompts for each extraction. Mage comes with 200+ predefined M&A clause types across 14 risk categories, automatic red and yellow flagging, and structured grid output ready to review. Every extraction cited to the source text. Export to Excel, PDF, and Word. The difference between building your diligence logic from scratch and having it built in.
Legal-Native Document Understanding
Mage does not just read documents. It understands how legal documents relate to each other. Amendment chains are detected and linked. Superseded provisions are identified. Cross-references between agreements are resolved. When Mage extracts a termination provision, it knows whether a later amendment changed it. Harvey treats each document independently.
Disclosure Schedules and Closing Checklists
Mage produces the deal-specific deliverables that Harvey cannot: auto-populated disclosure schedules with trigger analysis and provision-level guidance, closing checklists with template libraries and deadline tracking, and firm-branded diligence memos with executive summaries. These are the actual work products attorneys deliver to clients.
Variance Detection and Redline Comparison
Upload 100 customer agreements and Mage automatically identifies the standard form, detects which contracts deviate, and surfaces exactly which clauses differ and why they matter. Compare transaction document redlines with word-level change tracking and AI risk categorization. Harvey has no equivalent capability.
When to Use Each Tool
Harvey is a general legal AI. Mage is a diligence specialist. The right choice depends on the task.
Use Mage When
- You need structured extraction across 200+ M&A clause types with risk scoring
- You want to analyze an entire data room in a single workflow
- You need cross-document provision comparison and variance detection
- You need disclosure schedules, closing checklists, and deal-specific workflows
- You want firm-branded diligence memos with executive summaries
- You need one platform from data room to closing
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 beyond M&A
- You want a conversational AI interface for ad-hoc legal questions
Frequently Asked Questions
Common questions about Mage vs. Harvey
Harvey is a general legal AI platform with document Q&A, review tables, and drafting capabilities across practice areas. Mage is purpose-built for M&A due diligence. Both can upload and analyze documents, but Mage comes with 200+ predefined M&A clause types, automatic risk scoring, document classification, amendment chain detection, disclosure schedule automation, and closing-ready deliverables built in. Harvey requires you to define extraction logic from scratch for each project.
Harvey can upload documents to Vault and create ad-hoc review tables for extraction. However, it is a general tool where you build diligence logic from scratch each time. Harvey does not have predefined M&A clause types, automatic risk scoring, document classification by legal category, amendment chain detection, variance analysis across agreement sets, disclosure schedule automation, closing checklists, or firm-branded diligence memo generation. These are the specific capabilities that M&A transactions require.
For M&A contract review specifically, Mage provides purpose-built capabilities that a general legal AI does not: automated document classification across 50+ types, structured provision extraction with 200+ clause types across entire data rooms, cross-document comparison grids with automatic risk scoring, amendment chain detection, variance analysis, disclosure schedule automation, and firm-branded memo generation. 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, analysis, and deliverable generation for M&A transactions, while general AI tools support the broader legal work that surrounds deals.
Both platforms can handle large document sets. Harvey Vault supports up to 100,000 documents, and Mage processes entire data rooms concurrently. The difference is what happens after upload. Mage automatically classifies every document, detects amendment chains, extracts 200+ clause types with risk scoring, and presents results in a structured grid. Harvey requires you to define extraction queries manually. At scale, the difference between predefined M&A intelligence and ad-hoc prompting becomes significant.
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. The output is designed for the diligence workflow, not conversation.
Mage produces the actual deliverables attorneys send to clients: firm-branded diligence memos with executive summaries, variance reports, disclosure schedules with trigger analysis, closing checklists with deadline tracking, and redline comparisons with AI risk categorization. Harvey produces conversational responses and research summaries. The deliverable assembly from Harvey output is still manual.
See the Full Platform
Request a demo to see how purpose-built diligence software compares to general AI tools on your actual documents. From data room ingestion to closing-ready deliverables.
Request Demo