During VeeamON 2026 held in New York, Veeam Software unveiled a series of linked announcements, further aligning its data resilience strategy with the latest operational trends driven by artificial intelligence. The firm officially launched the Veeam DataAI Command Platform, gave a sneak peek of Veeam Data Platform v13.1 alongside the brand-new DataAI Resilience Module, and rolled out the Data and AI Trust Maturity Model. This model helps businesses evaluate their governance standards and practical deployment preparedness.

These brand-new upgrades enable Veeam to fill the prominent industry gap: as enterprises adopt AI technologies at high speed, they often lack sufficient means to secure, manage and restore core data supporting all AI-related systems.

Serving as a brand-new core architecture module, the Veeam DataAI Command Platform integrates data backup protection, cyber security, unified governance and compliance management, perfectly adapting to large-scale deployment scenarios of autonomous AI agents. Developed based on Veeam’s acquisition of Securiti AI, this platform seamlessly merges data security posture management tools with Veeam’s mature existing data resilience solutions.

Its core component is the DataAI Command Graph, an intelligent analysis layer that sorts out the connection logic among data resources, user identities and access permissions covering cloud platforms, SaaS services and local server environments. Different from traditional simple resource inventory tools, this graph supports refined data analysis, capable of pinpointing sensitive data content, risky access routes and potential hazard changes. It also establishes correlation analysis between production data and backup data, facilitating more intelligent data recovery and standardized governance processes.

This platform covers multiple core business modules. DataAI Security delivers full-spectrum insight into overall data and AI risk status. DataAI Governance implements bottom-layer data access restrictions instead of merely relying on agent-side rules, effectively lowering risks brought by authorized and unauthorized AI tools. DataAI Compliance ensures all data operations fit mainstream industry regulatory rules and can directly generate standard audit materials. DataAI Privacy executes real-time policy restrictions according to user identities and regional compliance requirements. DataAI Precision Resilience optimizes Veeam’s existing recovery functions and supports targeted fault fixes, letting enterprises solve partial data faults without conducting full-system rollback.

Veeam pointed out that this new platform caters to the major transformation of modern enterprise IT architecture. Nowadays, AI agents can freely access and process massive data, making core data rather than basic infrastructure the key security defense boundary.

Meanwhile, Veeam released advance information about Veeam Data Platform v13.1, which carries over 70 functional optimizations focusing on digital upgrade, safety reinforcement and faster data recovery. Its major highlight lies in cross-platform workload migration capability, with built-in support for OpenShift Virtualization and other mainstream environments, helping enterprises migrate business workloads without complicated architecture reconstruction.

The product also optimizes identity-based resilience functions, and the newly added Active Directory Forest Recovery function greatly enhances the recovery efficiency against identity invasion attacks. Its security features are further enriched, including upgraded multi-dimensional malware detection, post-quantum encryption algorithm adaptation and deeper docking with mainstream security systems.

This new version also focuses on cutting down enterprise operating costs and simplifying daily maintenance workflows. The newly added NAS file archiving and long-term data storage functions effectively lower overall storage expenses. Besides, its expanded threat scanning scope covers AWS, Azure, local NAS devices and Microsoft 365 business suites, accelerating risk identification and data recovery progress across hybrid and multi-cloud business layouts.

Launched based on the DataAI Command Platform, the brand-new DataAI Resilience Module builds a unified operation hub for standardized data resilience management. It provides an integrated management dashboard to display real-time protection status, system running conditions and overall business deployment readiness of all business environments.

Equipped with powerful global resource search and automatic inventory functions, operation managers can quickly confirm the protection status of all workloads and launch diverse recovery tasks, ranging from single file restoration, full-service site recovery to isolated data environment processing. This module also guarantees consistent operation specifications, reduces repeated configuration deviations and simplifies daily routine maintenance work.

Embedded intelligent AI agents can automatically finish repetitive daily work such as log sorting, work order distribution and storage resource scheduling. These automated functions effectively cut down manual operation pressure and boost overall response efficiency in large-scale enterprise business scenarios.

Apart from new platforms and product iterations, Veeam officially released the Data and AI Trust Maturity Model, aiming to help enterprises assess their actual AI management ability and practical application level. This model is formulated based on in-depth surveys of 300 senior enterprise management and technical executives, and clearly reflects the obvious imbalance between fast AI popularization and insufficient practical deployment capabilities.

Relevant research results show that AI technology has been widely applied in enterprise daily business processes, yet matched management mechanisms and traceable audit systems are still incomplete. Most enterprises are willing to expand AI business scale, but quite a number of them fail to provide valid audit-proof documents to verify the rationality of AI deployment. In addition, insufficient professional talents, difficult system integration and unclear regulatory requirements have become major obstacles restricting large-scale AI business promotion.

This maturity model conducts comprehensive assessment from 12 core dimensions and divides enterprise AI deployment level into five progressive stages, focusing on the actual execution effect of various management rules in real business scenarios. It sorts enterprise comprehensive readiness into four core sectors: full insight into data and AI systems, strict execution of safety and access rules, stable data backup and recovery guarantee, and qualified basic data resources for AI model training and iteration.

Enterprises can obtain quantified assessment results, industry horizontal comparison data and targeted optimization suggestions through this evaluation system, thus forming a clear implementation roadmap to achieve stable and accountable large-scale AI business deployment from preliminary trial application.

Veeam Data Platform v13.1 and DataAI Resilience Module are scheduled to be officially launched in the early third quarter of 2026, and will be delivered to global users via Veeam’s complete partner network. As an important part of Veeam’s overall layout, the DataAI Command Platform and Data and AI Trust Maturity Model will jointly promote the integrated construction of data protection, safety defense and AI standardized management, forming a complete unified operation management system.