Harvey is an AI legal platform that turns questions, documents, and workflows into cited, reviewable work product. It drafts and redlines, runs due diligence, and answers complex research with custom law-trained models and model orchestration. Built for firms and in-house teams, Harvey adds audit trails, SSO, logs, IP allow-lists, and data lifecycle controls—plus integrations for legal content and Microsoft stacks—so lawyers move faster without losing security or provenance.
Generate and refine contracts, clauses, briefs, and memos from firm templates or prompts. Harvey compares versions, flags risks, and proposes alternative language grounded in precedent, then links suggestions back to sources so reviewers can verify quickly. Teams move from first draft to partner review with fewer rewrites and clearer change rationales, keeping negotiations moving while preserving the firm’s playbook and jurisdictional nuances.
Upload data rooms or bundles and ask Harvey to surface key terms, exceptions, and anomalies across hundreds of files. It extracts obligations, dates, and parties; groups findings; and highlights deltas between similar contracts. Reviewers can drill from summaries to passages and export checklists for handoff. The result is faster, more consistent diligence cycles with traceable evidence—useful for M&A, financing, vendor risk, and policy audits where coverage and speed both matter.
Ask complex questions and get concise answers with inline citations to primary sources. Harvey routes tasks to custom case-law–tuned models and can incorporate partner databases where licensed, returning quotes you can expand and verify. Use it for scoping arguments, comparing jurisdictions, or briefing partners without hours of tab-hopping. The cited output reads like a mini-memo that survives scrutiny and accelerates downstream writing and review.
Harvey chooses the best model and workflow per task—drafting, search, or extraction—and collapses tools into one interface that mirrors how lawyers work. Instead of juggling multiple apps, users ask in natural language and Harvey routes to data, models, or playbooks as needed. This reduces context switching, improves answer quality, and keeps a single history of steps taken so results are reproducible and easier to audit across matters.
SAML SSO, audit logs, IP allow-listing, and contractual security addenda align with SOC/ISO expectations. Deploy on Azure with OpenAI models and add licensed legal content via partners, while Word/SharePoint add-ins keep work inside existing stacks. Data access and retention controls, plus incident SLAs, help satisfy client and regulatory reviews—so adoption doesn’t stall on security questionnaires or siloed pilots that can’t scale firm-wide.
Law firms, ALSPs, and in-house legal teams that need faster drafting, diligence, and research with strong governance. Ideal for transactional, litigation, and compliance groups standardizing playbooks; knowledge teams curating sources; and IT/security leaders who require SSO, logging, and contractual controls. Also useful for innovation teams piloting agents that must produce cited work product and fit Microsoft-centric environments.
Replaces tab-hopping across research tools, manual version diffs, and inconsistent diligence spreadsheets with one system that drafts, cites, and audits. It solves slow first drafts, brittle copy-paste reviews, and security friction by unifying models, evidence, and controls. Lawyers get trusted, explainable outputs that slot into Word and matter systems; leaders get repeatable workflows and clearer risk posture—moving AI from sandbox experiments to firm-wide productivity.
Visit their website to learn more about our product.
Grammarly is an AI-powered writing assistant that helps improve grammar, spelling, punctuation, and style in text.
Notion is an all-in-one workspace and AI-powered note-taking app that helps users create, manage, and collaborate on various types of content.
0 Opinions & Reviews