Wald

Wald is an enterprise AI security platform with endpoint AI DLP and a secure workspace for approved LLMs, helping control usage and sensitive data exposure.

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Overview

Wald is an enterprise AI security platform focused on two related jobs: preventing data leaks when employees use AI tools, and giving teams secure access to leading language models inside a governed workspace. The product is presented as both an AI DLP layer and an LLM Pack, so organizations can choose between protecting existing AI usage or centralizing access to approved models.

The AI DLP product works at the endpoint, where it inspects prompts locally, classifies sensitive content using contextual intelligence, and applies policies such as allow, monitor, warn, and block. The LLM Pack provides a managed environment for ChatGPT, Claude, Gemini, Grok, and other models, with prompt sanitization, access controls, audit logs, and end-to-end encryption.

Core capabilities

On-device AI DLP

Inspect AI prompts locally at the endpoint so sensitive content can be detected before it reaches external model providers.

Context-aware detection

Classify prompts by context and intent instead of relying only on regex rules, which helps catch sensitive content that does not match simple patterns.

Flexible policy enforcement

Apply allow, monitor, warn, and block actions through a single policy engine across devices, browsers, data types, teams, and AI apps.

Prompt sanitization and local restoration

Replace sensitive details with placeholders during the interaction, then restore the original data locally after the response is returned.

Audit trails and reporting

Track AI usage with audit logs, visibility dashboards, and reporting tools for governance and compliance review.

Managed multi-model access

Give teams one subscription or workspace for multiple leading AI models, including ChatGPT, Claude, Gemini, and Grok.

Common use cases

Govern unsanctioned AI usage
Use the endpoint DLP layer to see how employees are using AI tools, identify shadow AI activity, and enforce policy without blocking productive work unnecessarily.
Provide secure access to approved LLMs
Deploy the LLM Pack when teams need a controlled workspace for regular use of multiple AI models and want a single place to manage access, logs, and prompts.
Protect sensitive prompts and documents
Apply contextual sanitization and local redaction when employees need to work with sensitive business, customer, or health information in prompts.
Support security and compliance oversight
Use audit trails, searchable logs, and admin controls to support internal review, governance processes, and compliance evidence gathering.
Adapt DLP for AI-specific workflows
Let teams work with AI models while retaining endpoint visibility and policy control, especially where existing DLP tools were built for email or file transfers rather than AI prompts.

Pros and Cons

Pros

Offers endpoint-level AI DLP that works locally rather than only at the network layer.
Uses contextual classification, which the site says is more precise than pattern-based matching alone.
Supports multiple policy actions, including allow, monitor, warn, and block.
Provides a separate secure workspace for teams that want direct access to multiple leading models.
Includes audit logs, reporting, and admin controls for governance and review.

Cons

The source does not provide a complete integration list or a broad set of source-system connectors.
Pricing and packaging are only partially described, so buyers may need to contact sales or review the enterprise terms for full commercial details.
Several security and compliance claims are presented by the vendor, but the site does not provide a full technical specification for independent evaluation.

FAQ

What is the difference between Wald AI DLP and Wald LLM Pack?

Wald offers two main products: AI DLP for monitoring and controlling employee use of AI tools at the endpoint, and Wald LLM Pack for giving teams secure access to multiple AI models in a managed workspace.

How is Wald deployed?

The source says Wald offers flexible deployment models. Most enterprises start with a SOC 2 compliant SaaS application, while the DLP solution is installed at each endpoint and the SaaS app can be accessed through a browser.

How does Wald protect prompts and data?

Wald says its DLP layer uses contextual intelligence rather than only pattern matching. It can allow, monitor, warn, or block sensitive usage, and it supports localized prompt sanitization so the AI can still process a request without exposing secrets to the model provider.

Does Wald store or access customer data?

The pricing page says Wald uses end-to-end encryption and has a zero data retention policy that can be adjusted by the customer depending on governance needs. It also states that no Wald employee can access customer data.

What AI tools does Wald work with?

The source does not list a full integration catalog. It does say the AI DLP works across major AI tools and browsers, including ChatGPT, Claude, Gemini, Copilot, Grok, and other AI tools mentioned on the product pages.

Quick Facts

Category: AI security / AI DLP
Primary product modes: AI DLP and secure LLM workspace
Platform: Endpoint agent plus browser-accessible SaaS
Main AI models mentioned: ChatGPT, Claude, Gemini, Grok, Copilot
Pricing signal: Enterprise pricing and a paid per-seat plan are referenced on the site
Website: wald.ai