VAST Data tackles the enterprise AI trust gap

The New Stack

by Frederic Lardinois

February 25, 2026

AI-Generated Deep Dive Summary

VAST Data is addressing the growing challenge of trust in enterprise AI adoption by introducing PolicyEngine, a new tool designed to establish guardrails at the infrastructure level. While many organizations focus on model quality as the primary barrier to deploying AI agents, VAST argues that trust—specifically, trust in how models are trained, what data they access, and how they interact with other systems—is the true bottleneck for widespread adoption. This issue is particularly critical for enterprises looking to scale AI in production environments. VAST, a rapidly growing player in data and AI infrastructure, has developed PolicyEngine as part of its broader strategy to build an "AI Operating System" that combines storage, database, and compute capabilities. The tool acts as a decisioning framework, allowing organizations to define policies that govern agent behavior, interactions with other tools, and access to sensitive data. By integrating AI-powered transformations, PolicyEngine can redact or reformat data before it reaches AI models, ensuring that sensitive information remains protected. Additionally, all actions are logged in tamper-proof audit logs, which is especially valuable for industries subject to regulation. The introduction of PolicyEngine marks a significant shift in how enterprises approach AI deployment. Traditional guardrails are often added retroactively, but VAST’s solution embeds trust and security at the infrastructure level, making it easier to manage and enforce policies across distributed systems. This approach not only addresses immediate concerns around model behavior but also positions organizations for more scalable and reliable AI deployments in the future. For DevOps professionals and cloud engineers focused on building robust AI pipelines, tools like PolicyEngine represent a critical step toward bridging the trust gap that currently hinders enterprise adoption of AI technologies.

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Originally published on The New Stack on 2/25/2026