Veeam announced its new DataAI Command Platform at VeeamON 2026, an initiative that aims to extend the company’s offerings beyond traditional backup and recovery. The company defines it as a trusted unified infrastructure for data and Artificial Intelligence, designed for a scenario where autonomous agents are no longer just lab promises but active components within business processes.
The announcement follows the acquisition of Securiti AI, a deal valued at around $1.73 billion according to Reuters, which strengthens Veeam’s position in data security, governance, privacy, and AI trust. The strategic takeaway is clear: data protection no longer ends with backup. In agent-based AI environments, it’s also critical to know what data exists, who can access it, which agents are using it, what risks are involved, and how to restore only what is affected when something goes wrong.
From Backup to Operational Trust in AI
For years, Veeam has built its reputation on data resilience: backups, recovery, continuity, ransomware protection, and availability. With DataAI Command Platform, the company seeks to expand into a broader layer: integrating data, access, identities, and AI within a single control platform.
Veeam’s core idea is based on a simple but uncomfortable truth for many organizations. The infrastructure to deploy AI already exists: models, APIs, cloud platforms, GPUs, agents, and automation tools. What’s less established is the infrastructure needed to trust that AI when it interacts with sensitive corporate data. Anand Eswaran, CEO of Veeam, summarizes this by stating that the security control point is now the data itself, because agents need access to it to operate.
The company highlights the problem in what it calls the “agentic era.” According to their data, autonomous agents now outnumber human employees at a ratio of 82 to 1, with 97% of them having excessive privileges. These figures, provided by Veeam, should be viewed in context, but they reflect a real cybersecurity concern: many organizations are creating machine identities, agents, connectors, and automations faster than they can govern them.
The danger isn’t just an agent making a mistake; it can also access sensitive information it shouldn’t, combine data from different systems, act with overly broad permissions, or become a attack vector if its credentials are exposed. In such scenarios, traditional perimeter security is insufficient. Security needs to move closer to the data, understand its sensitivity, and enforce policies at the source.
Six Components of a Control Platform
DataAI Command Platform comprises six integrated capabilities. The first is DataAI Command Graph, an intelligence layer with over 300 connectors for cloud, SaaS, and on-premise environments. Its goal isn’t just to discover databases, but to identify specific files containing sensitive information, associated access controls, and changes that could pose risks. Veeam also emphasizes that this graph covers both production systems and backup environments, a key difference from solutions focused solely on live data.
The second component is DataAI Security, built on Securiti AI’s DSPM (Data Security Posture Management) technology. DSPM has become a vital category because many companies lack full visibility of sensitive data across clouds, SaaS applications, internal repositories, and backups. Veeam aims to unify this visibility with identity intelligence and resilience trust.
The third component, DataAI Governance, addresses a specific challenge in agentic AI: governing data not only at runtime but ensuring that sources are protected from the outset. If data is safeguarded at its origin, both authorized and unauthorized agents, as well as unknown or non-sanctioned agents, are limited by policies directly applied to the source.
Fourth is DataAI Compliance, which maps across more than 100 regulatory frameworks, including the European AI Regulation, DORA, GDPR, HIPAA, NIST, and AI RMF. This component addresses the increasing need for CIOs, CISOs, DPOs, and boards to generate auditable evidence of how data used by AI systems is governed.
The fifth capability, DataAI Privacy, focuses on enforcing privacy policies in real time by user and jurisdiction. Veeam describes a People Data Graph designed to unify structured and unstructured personal data in hybrid and multi-cloud environments. The sixth, DataAI Precision Resilience, offers targeted recovery, undoing only what has been affected without rolling back entire systems.
| Capability | What It Provides |
|---|---|
| DataAI Command Graph | Granular visibility into data, access, identities, and backups |
| DataAI Security | Data and AI security posture management |
| DataAI Governance | Source control for data used by agents |
| DataAI Compliance | Auditable evidence across 100+ regulatory frameworks |
| DataAI Privacy | Privacy policies by user, data, and jurisdiction |
| DataAI Precision Resilience | Targeted recovery for errors, attacks, or undesired actions |
Microsoft 365, Modules for Existing Customers, and Maturity Model
Alongside the platform, Veeam announced a preview of Veeam Intelligence ResOps for M365, bringing DataAI Command Graph’s intelligence to Microsoft 365, one of the most widely used SaaS platforms in enterprises. They also introduced a new DataAI Resilience Module for current Veeam Data Platform users, enabling access to cross-cutting intelligence and agent capabilities without requiring a full migration.
The company also previewed Veeam Data Platform 13.1 and a Data and AI Trust Maturity Model. Based on data from over 300 CIOs and CISOs, this model structures a path with four pillars, twelve dimensions, forty-nine subdimensions, and five levels of maturity. Its goal is to help organizations evaluate their current status and develop a roadmap for more secure AI adoption.
This aligns with broader market trends. Backup, cybersecurity, data governance, and observability providers are converging around AI, recognizing that agents cross traditional categories: they need identity, access, data, context, permissions, traceability, and recovery capabilities. This convergence is prompting a unified approach across disciplines traditionally managed separately.
For Veeam, the opportunity is clear. With over 550,000 customers across more than 150 countries, its large installed base positions it well to extend this layer of trust to organizations already using its resilience solutions. However, challenges remain to seamlessly integrate Securiti AI, simplify user experience, prevent the platform from becoming another complex dashboard, and demonstrate that precise recovery provides tangible benefits in incidents involving AI, ransomware, or automation errors.
The rise of agentic AI is compelling companies to reconsider a fundamental question: not just whether they can deploy agents, but whether they can trust what those agents do with their data. Veeam aims to position itself precisely at this intersection. Its message is that resilience no longer just means system recovery, but also involves understanding, governing, and protecting data at every stage of interaction with AI.
Frequently Asked Questions
What is Veeam DataAI Command Platform?
A platform introduced by Veeam to unify resilience, security, governance, compliance, privacy, and AI trust around data, access, identities, and agents.
Why is it related to Securiti AI?
DataAI Command Platform results from integrating Securiti AI, acquired by Veeam, with Veeam’s existing resilience and data recovery capabilities.
What problem does it aim to solve in agentic AI?
It seeks to control which data agents can access, manage identities, assess risks, and enable precise recovery if incidents involving agents, users, or attackers occur.
What does it offer to current Veeam customers?
Veeam is launching a DataAI Resilience Module for existing Veeam Data Platform users, providing cross-cutting intelligence and agent functionalities without requiring a complete migration.
via: veeam