Harvey AI processes 700,000 tasks daily across 1,300 organizations

Harvey AI processes 700,000 tasks daily across 1,300 organizations. But "tasks" is vague. What are lawyers actually using Harvey for? The answer: M&A due diligence, contract review, litigation document analysis, regulatory compliance, and antitrust filing prep — the high-volume, high-stakes workflows where AI creates measurable efficiency gains.

This isn't a feature list. These are the production workflows running across Harvey's platform today, processing 50 million contract terms per week through 25,000 custom-built agents. Here's what actually works.

Harvey AI for M&A due diligence

M&A due diligence is Harvey's flagship use case — and where the platform delivers the clearest ROI.

The workflow: Harvey's agents ingest virtual data rooms containing thousands of documents — contracts, financial statements, corporate records, IP filings. The agents automatically identify material contracts, flag change-of-control provisions, extract assignment restrictions, map termination rights, and identify non-compete obligations across the entire data room.

What makes it work: Traditional due diligence requires teams of associates manually reviewing every document. A mid-market deal might involve 5,000-10,000 documents. Harvey's agents handle the bulk classification and extraction, reducing first-pass review time by 40-60% while catching provisions that human reviewers miss due to fatigue.

In production: A&O Shearman, Harvey's flagship partner, uses Harvey extensively for cross-border M&A due diligence. The platform's ability to process documents across multiple languages and jurisdictions simultaneously is a capability no human team can match at speed.

Best for: Am Law 100 firms, Big Four advisory practices, and corporate development teams running multiple simultaneous deals.

Harvey AI for contract review and analysis

Harvey processes 50 million contract terms per week — making contract review the platform's highest-volume use case.

The workflow: Upload contracts (NDAs, MSAs, employment agreements, leases, licensing agreements). Harvey's agents extract key terms, compare against your firm's standard playbook, flag non-standard provisions, identify missing clauses, and generate redline suggestions. The output is a structured analysis that a senior associate would normally take 2-4 hours to produce.

What makes it work: Harvey's Agent Builder lets firms encode their specific contract standards into the review process. Your NDA playbook, your MSA risk tolerance, your lease review checklist — all built into agents that apply your standards consistently across every review.

Real impact: A firm reviewing 200 NDAs/month saves approximately 400-800 associate hours monthly — worth $100,000-300,000 at typical billing rates. That's where Harvey's $1,200/seat/month starts looking reasonable.

Best for: Firms with high-volume transactional practices, in-house legal teams managing vendor contracts, and any organization processing 100+ contracts monthly.

Harvey AI for litigation document review

Document review in litigation is the legal industry's most expensive manual process — and Harvey's agents are built to attack it.

The workflow: Ingest production sets from opposing counsel. Harvey's agents classify documents by relevance, apply issue coding, flag privileged communications, identify hot documents, and generate privilege logs. The agents handle the first-pass triage that traditionally requires teams of contract attorneys billing at $75-150/hour.

What makes it work: Harvey's models understand legal context — they can distinguish between a casual email mentioning a product and a document materially relevant to a patent claim. The classification isn't keyword matching; it's contextual analysis trained on legal corpora.

Cost comparison: A 500,000-document review using contract attorneys at $100/hour might cost $2-5 million. Harvey's agents handling first-pass triage can reduce that by 30-50%, with human reviewers focusing on flagged documents and edge cases.

Best for: Litigation-intensive firms, class action practices, and any firm regularly handling large-scale discovery.

Harvey AI for regulatory compliance

Regulatory compliance is a use case where Harvey's Agent Builder creates compounding value over time.

The workflow: Agents monitor regulatory changes across specified jurisdictions and agencies. When new rules, guidance, or enforcement actions appear, the agents map requirements against client obligations, flag compliance gaps, and generate action items. This transforms compliance from reactive fire-fighting to proactive monitoring.

What makes it work: Regulatory landscapes are massive and constantly shifting. Financial services firms alone must track regulations from the SEC, CFTC, FINRA, OCC, Fed, and state regulators — plus international equivalents. No human team can monitor all sources simultaneously. Harvey's agents can.

Practical application: A banking client's compliance team uses Harvey to monitor changes across 15 jurisdictions. When a new regulation drops, the agent identifies affected business lines, maps requirements to existing policies, and generates a gap analysis — work that previously took a compliance team 2-3 weeks, delivered in hours.

Best for: Financial services firms, healthcare organizations, multinational corporations, and regulatory practices serving heavily-regulated industries.

Harvey AI for antitrust filing analysis

Antitrust work involves massive document volumes, multi-jurisdictional requirements, and tight filing deadlines — exactly the conditions where Harvey's agents excel.

The workflow: Harvey's agents analyze merger notifications across jurisdictions, identifying potential competition concerns before filing. They cross-reference proposed transactions against precedent decisions, market definition frameworks, and agency guidance. For HSR filings in the U.S. and equivalent filings internationally, agents prepare initial drafts of narrative responses and document compilations.

What makes it work: Antitrust analysis requires synthesizing information across thousands of internal documents, market data, and regulatory precedent simultaneously. Harvey's ability to process and cross-reference at scale — the same architecture that handles 50 million contract terms weekly — is uniquely suited to this complexity.

Real-world example: Multi-jurisdictional merger clearance that requires coordinated filings in the U.S. (DOJ/FTC), EU (DG COMP), UK (CMA), and other authorities. Harvey's agents ensure consistency across filings while adapting to jurisdiction-specific requirements.

Best for: Am Law 50 antitrust practices, Big Four transaction advisory teams, and multinational corporations with regular M&A activity requiring antitrust clearance.

The Bottom Line: Harvey's strongest production use cases are M&A due diligence, high-volume contract review, and litigation document analysis — workflows where processing 50M+ terms weekly at enterprise scale creates undeniable efficiency gains.