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ZeroDrift launches Guard for Agents compliance service

ZeroDrift launches Guard for Agents compliance service

Key takeaway

  • ZeroDrift launched Guard for Agents, a compliance service for AI communications. It turns written policies into rules that check agent messages before sending.

  • Each validation costs one cent.

  • Interest is growing in voice agents for financial services and healthcare.

3 Key Points

  1. What happened

    ZeroDrift Inc. today introduced Guard for Agents, a service that converts written company policies into enforceable rules to check AI agent communications before they reach customers. The product builds on Command, the company's existing compliance control center, and is priced at one cent per validation.

  2. Why it matters

    The service addresses the gap between policies stored in documents and the messages AI agents actually generate, operating at what founder and CEO Kumesh Aroomoogan calls the "pre-send layer." Checks run in milliseconds, and interest is emerging from voice agent developers in financial services and healthcare, as well as AI startups selling into regulated industries.

  3. What to watch

    The policy connectors use Model Context Protocol to import documents from Notion Labs Inc., Linear Orbit Inc. and Google LLC's Drive. Each check uses Anchor 3.0-Preview, a proprietary model post-trained on attorney-labeled data. ZeroDrift plans third-party benchmarks to substantiate claims of faster and less expensive validation than general-purpose models.

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Context & Analysis

ZeroDrift's launch extends its compliance technology, previously centered on Command, into the agent workflow space. The company positions Guard as sitting between the generation of a message and its delivery, catching violations in real time rather than after the fact. This pre-send positioning is notable because it targets a specific moment in the AI content pipeline where policy gaps commonly occur.

The business model reflects an operating-cost approach: one cent per validation, with checks covering email, text and Slack posts. Implementation is designed to avoid requiring developers to rewrite policies in proprietary languages — instead, a small language model identifies rules from imported policy documents, and customers can inspect and select rules in a visual interface. The underlying model, Anchor 3.0-Preview, was post-trained on attorney-labeled data, and the company logs enforcement decisions for audit purposes.

Aroomoogan indicated the company is considering expansion beyond written communications into voice agents, responding to demand in financial services and healthcare. The technology also works across conventional marketing and CRM systems without a language model, though rewrites are limited to machine-generated content. Notable for potential enterprise buyers, ZeroDrift has not yet released latency measurements or independent performance results, though it plans third-party benchmarks in the future.

FAQ

How does Guard for Agents work?
Developers send an agent's output to a validation endpoint. The service checks text against rules and returns violation details, including severity. Depending on policy, it can supply a replacement, recommend blocking, or escalate for human review.
What types of content can be blocked?
Messages containing confidential financial information or promising a guaranteed investment return could be blocked. Customers configure how violations are handled, and can opt for automated handling without human intervention.
Does the service only work with AI language models?
No. The technology can also check communications from conventional marketing and customer relationship management systems. Automatic rewrites apply to machine-generated content, not human-authored messages.
SiliconANGLE AIRead Original Article

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