SOC 2 for Legal AI
Definition
SOC 2 (System and Organization Controls 2) is an auditing framework developed by the AICPA that evaluates a service provider's controls for security, availability, processing integrity, confidentiality, and privacy. For legal AI platforms, SOC 2 compliance demonstrates that the vendor has implemented and maintained the security controls necessary to protect sensitive legal data.
SOC 2 compliance is not a certification that a vendor passes or fails; it is an independent audit by a qualified CPA firm that evaluates whether a vendor's controls meet the Trust Services Criteria. The audit examines the design and operating effectiveness of controls across five categories: security (protecting against unauthorized access), availability (ensuring the system is operational), processing integrity (ensuring accurate processing), confidentiality (protecting confidential information), and privacy (protecting personal information).
For law firms evaluating AI vendors, SOC 2 compliance is a critical baseline. It provides independent assurance that the vendor has implemented appropriate security controls and that those controls are actually functioning as designed. A SOC 2 Type II report, which covers a period of time rather than a point in time, provides stronger assurance because it demonstrates sustained compliance.
However, SOC 2 is a baseline, not a ceiling. Legal AI platforms handle uniquely sensitive data, including privileged communications, litigation strategy, and confidential client information, that may warrant controls beyond what SOC 2 requires. Firms should look for SOC 2 compliance as a minimum requirement and then evaluate additional security measures specific to legal data handling.
How Irys approaches this
Irys maintains SOC 2 Type II compliance and implements additional security controls specifically designed for the sensitivity of legal data, including privileged communications and client confidential information.
Related terms
Zero Data Retention
Zero data retention is a security policy in which an AI platform does not store user queries, uploaded documents, or generated outputs on its servers after processing is complete. For law firms, this policy ensures that confidential client information is not retained in third-party systems where it could be exposed through data breaches or used to train AI models.
SecurityTenant Isolation
Tenant isolation is a security architecture in which each customer's data is logically or physically separated from every other customer's data within a multi-tenant platform. In legal AI, tenant isolation ensures that one firm's confidential information, work product, and AI interactions are completely inaccessible to other firms using the same platform.
SecurityAttorney-Client Privilege and AI
Attorney-client privilege protects confidential communications between a lawyer and client made for the purpose of seeking or providing legal advice. When lawyers use AI tools, privilege concerns arise because sharing privileged information with a third-party technology provider could be construed as a waiver of the privilege if adequate confidentiality protections are not in place.
SecurityEnd-to-End Encryption in Legal
End-to-end encryption is a security method in which data is encrypted on the sender's device and can only be decrypted by the intended recipient, remaining encrypted throughout transmission and storage. In legal AI, end-to-end encryption protects confidential client data, privileged communications, and work product at every stage of processing.
See SOC 2 for Legal AI in action
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