Context-aware AI data security for enterprises governing employee use of LLMs and AI applications.
Wald is an enterprise AI security platform that helps organizations govern employee interactions with large language models and other AI applications. Its endpoint AI DLP analyzes prompts and documents in context, identifying sensitive information and applying policies before that content reaches an AI model. The platform is designed to add visibility and controls to existing AI use, including unsanctioned tools, while allowing teams to keep using approved models. Wald also offers a secure AI workspace that brings multiple leading LLMs into one interface with prompt sanitization. Security teams can use centralized activity records and reporting to review AI usage and policy enforcement.
Uses locally deployed small language models to classify the meaning and intent of prompts and documents, rather than relying only on fixed patterns. Sensitive content can be sanitized before it reaches an external model.
Applies controls at the point where employees interact with AI, including desktop applications, browser-based tools, coding assistants, and embedded AI.
Provides security teams with records and reporting on AI activity, detected sensitive data, sanitization, and policy enforcement.
Extends oversight beyond chat to AI agents and their tool interactions, including MCP connections, where agents can access files, APIs, or databases.
Offers a workspace for accessing multiple leading LLMs with built-in prompt sanitization and centralized administrative controls.
Supports centralized policy enforcement and classification to help organizations manage AI use according to their governance requirements.
Payments teams can let employees use AI for tasks such as debugging, case summaries, or operational analysis while sanitizing payment details, customer identifiers, credentials, and transaction information in prompts.
Security and compliance teams can review employee AI activity, enforce organizational policies, and retain interaction records for investigations and compliance reviews.
Schools can review staff AI activity and apply controls to sensitive information used in academic and administrative workflows.
Organizations that want a dedicated environment for AI use can give employees access to multiple models through one workspace with prompt sanitization and administrative controls.
Wald describes using locally deployed small language models to classify context and intent, supplementing pattern-based detection. Its safeguards can identify and sanitize sensitive content in prompts and documents before they reach an AI model.
Yes. Endpoint AI DLP is described as governing interactions across existing AI licenses and applications, including browser and desktop tools, coding assistants, embedded AI, and personal or unmanaged AI accounts.
Wald says its governance extends to agents and the tools they call, including MCP connections, so security teams can oversee interactions beyond a chat interface.
The DLP solution is installed at endpoints, while the SaaS application is accessed through a browser. Wald offers deployment models matched to an organization’s risk profile.
The LLM Pack has a listed $19.99 monthly subscription. AI DLP pricing is tailored to the deployment and arranged through sales.
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