# Legal AI for enterprise > GenieAI deploys at enterprise scale - drafts, reviews, and negotiates MSAs, DPAs, and procurement contracts with SOC2, ISO 27001, and SAML SSO out of the box. **Company type:** Enterprise Govern the contract motion across thousands of agreements without scaling headcount ## Enterprise-grade legal AI, deployed across the org GenieAI is the AI legal assistant trusted by 200,000+ business teams. We draft, review, and negotiate every contract across an enterprise portfolio - MSAs, DPAs, procurement, employment - with current-law accuracy across 150+ jurisdictions, deployed with SSO, audit trail, and tenant-isolated data. - Auto-draft MSAs, DPAs, and enterprise procurement agreements - Enforce playbook fidelity across thousands of contracts and counterparties - Tenant-isolated by default - SOC2 + ISO 27001 + SAML SSO ## Use cases for Enterprise ### Word Add-in GenieAI inside Microsoft Word - review, redline, and draft contracts without leaving the document. [https://www.genieai.co/use-case/word-add-in](https://www.genieai.co/use-case/word-add-in) ### Ask your Document Ask plain-English questions about any contract and get cite-grounded answers tied back to the exact clause. [https://www.genieai.co/use-case/ask-your-document](https://www.genieai.co/use-case/ask-your-document) ### Review & Negotiate Spot risk, understand obligations, and let Genie redline counterparty markup against your playbook. [https://www.genieai.co/use-case/review-negotiate](https://www.genieai.co/use-case/review-negotiate) ### AI Contract Assistant Your AI legal teammate - drafts, reviews, and remembers prior decisions across every contract your team touches. [https://www.genieai.co/use-case/ai-contract-assistant](https://www.genieai.co/use-case/ai-contract-assistant) ### Create Contracts Generate enforceable contracts from a plain-English brief - across 150+ jurisdictions, with pre-vetted clauses. [https://www.genieai.co/use-case/create-contracts](https://www.genieai.co/use-case/create-contracts) ## How does GenieAI compare to ChatGPT? | Capability | GenieAI | Claude | ChatGPT | | --- | --- | --- | --- | | Conversational interface | Yes | Yes | Yes | | Can upload docs & PDFs | Yes | Yes | Yes | | Review against your playbook rules | Yes | Yes | No | | Edit and negotiate in tracked changes | Yes | No | No | | Collaborative legal editor for teams | Yes | No | No | | Compare against a proprietary legal dataset | Yes | No | No | | Manage complex deals with Eidetic Intelligence | Yes | No | No | | Develop an org-wide legal brain | Yes | No | No | | Save templates, playbooks, insights | Yes | No | No | ## Enterprise FAQs ### How do we keep contract positions consistent when every business unit negotiates its own deals? By setting the positions once as a playbook and reviewing every incoming contract against it, rather than relying on each team to remember them. Legal defines what is acceptable, what is a permitted fallback, and what must escalate. Consistency is a risk control rather than an administrative preference. Once a hundred agreements carry a hundred slightly different liability caps, nobody can answer a simple question about total exposure without reading all of them. ### Can commercial teams run their own contracts without legal losing control? Yes, and that is the intended design. Agreements that sit inside the agreed positions proceed without joining a legal queue, and anything outside them is flagged and routed to legal rather than quietly accepted. The control is the playbook rather than the queue. Legal keeps authorship of the standards while giving up the bottleneck. ### What should be in place before rolling out AI contract review across an enterprise? A documented playbook, a clear escalation path, and an agreed position on what may be approved without a human reading it. GenieAI is ISO 27001 certified, documents stay in your tenant, and they are not used to train models. The governance questions are usually harder than the technical ones. The decision that matters is which positions the business will accept automatically. ### How do we handle a counterparty that insists on using their own paper? Review it against your playbook rather than against a blank page. Incoming paper is marked up to your agreed positions, with every clause that falls outside them flagged, so the negotiation starts from your standards even on someone else's document. Most contract risk arrives on counterparty paper, which is exactly where a manual review is least consistent. ### How do we review terms consistently across hundreds of suppliers? Your buying standards become the playbook, and every incoming [supplier agreement](https://www.genieai.co/en-us/template-type/supplier-agreement) or [vendor agreement](https://www.genieai.co/en-us/template-type/vendor-agreement) is reviewed against it, so the terms you accept differ only where you decided they should. At that scale the exposure is rarely one bad contract. It is the same weak clause repeated across a category without anyone noticing. ### How does GenieAI deploy across an enterprise? GenieAI deploys via SSO, SCIM provisioning, and tenant-isolated infrastructure. Documents and metadata never leave your tenant. Enterprise customers run with dedicated infrastructure where regulation requires. ### Does GenieAI support enterprise governance and audit? Yes. Role-based access control, approval workflows, immutable audit logs, and integration with enterprise systems (Salesforce, Workday, ServiceNow). Every contract action is traceable for audit. ### What security and compliance commitments does GenieAI hold? GenieAI is ISO 27001 certified and operates under GDPR. Customer documents never train models and are not shared with third-party LLMs. Security questionnaires are pre-completed and available on request. --- This is the Markdown representation of [https://www.genieai.co/legal-ai-for/enterprise](https://www.genieai.co/legal-ai-for/enterprise), provided for AI agents and crawlers. The HTML page is canonical. See [/llms.txt](https://www.genieai.co/llms.txt) for the full content map.