Securiti helps enterprises use their data with AI safely. Its DataAI Command Platform finds and classifies sensitive data across hybrid multicloud and SaaS environments, controls who and what can reach it, and governs how it flows into copilots, models and AI agents, while automating the privacy and compliance work that follows. It is aimed at security, privacy and data teams who share responsibility for the same data.
The problem it addresses is that the data AI needs is the same data privacy law and security teams must protect, so getting value from AI depends on knowing exactly what that data is and who touches it.
At A Glance
| Vendor | Securiti (part of Veeam Software) |
|---|---|
| Category | Data security, DSPM, AI security and governance, privacy automation |
| Identities covered | Users accessing data, AI agents, copilots and models |
| Deployment | Unified platform across hybrid multicloud and SaaS, with 1000+ integrations |
| Agentic AI | Agent Commander, security for AI agents and copilots, LLM firewalls |
| Founded | 2019 |
| Market classification | Data Security; also Agentic AI Identity |
What Securiti Does
Enterprises want AI assistants and agents to work with their data, but that data is scattered across clouds and SaaS apps, much of it sensitive and subject to privacy law. Securiti’s approach is to build one picture of every data and AI object and using it to drive security, privacy, governance and compliance controls. Security, privacy and data teams then work from the same inventory instead of keeping separate ones, and a control set once, such as a least privilege rule or a consent record, applies wherever the data travels, including into the context an AI model receives.
Products
Secure
The Secure group is for security teams who need to know where sensitive data sits and who can reach it.
- Data Security Posture Management: protects sensitive data everywhere from hybrid multicloud to SaaS.
- Data Discovery and Classification: finds shadow and cloud-native assets and classifies the data in them.
- Data Access Intelligence and Governance: monitors user access to data and enforces least privilege.
- Security for AI Agents and Copilots: applies data security controls so enterprises can adopt agentic AI without exposing sensitive data.
- Agent Commander: discovers AI agents and models with their entitlements, tracks agent reads, writes and deletes at file level, blocks prompt injection and data leakage with runtime guardrails, and restores only the affected files when an agent makes a mistake. It is offered through early access.
- Security for Amazon Q: data access governance, file-level risk intelligence, classification and remediation policies for Amazon Q.
- Breach Impact Analysis, Data Flow Governance, Data Minimization and Compliance Management.
Build
Build is for teams putting enterprise data behind generative AI. Safe Enterprise AI Copilots enforce data rules wherever a copilot reads, and Context-aware LLM Firewalls guard retrieval, responses and prompts. Data Vectorization and Ingestion, Data Curation and Sanitization for AI, and Unstructured Data Governance prepare files for vector databases and model training without carrying sensitive content along.
Govern
Govern serves data owners and AI governance teams with a Data Catalog, Data Lineage and Data Quality, Data Access Governance to prevent unauthorised use of sensitive data, and AI Governance to set controls for safe adoption of AI, including generative AI.
Automate
Automate takes the manual work out of privacy programmes: Data Mapping Automation, Data Subject Request Automation, Assessment Automation, Consent Management, Mobile App Consent Management, Breach Management and a Privacy Center.
How It Works
All products run on one platform, described as a Unified Data Command Center for data intelligence, security, privacy and compliance.
| Component | What it does |
|---|---|
| DataAI Command Graph | Captures contextual information for every data and AI object automatically and works in real time, feeding classification, lineage and continuous risk scoring for the products above. |
| Integrations layer | More than 1,000 pre-built integrations connect the platform to data systems across hybrid multicloud and SaaS. |
| Runtime path | For AI traffic, Agent Commander and the LLM firewalls sit in line between copilots or agents and the data they reach, so policy applies at the moment of each request rather than only in scheduled scans. |
Identities And Systems Covered
| Users | Human access to data, monitored and held to least privilege. |
|---|---|
| AI agents and models | Catalogued with full entitlement and data access context. |
| Copilots | M365 Copilot, Amazon Quick and Gemini Enterprise, with enterprise data made AI-ready for each. |
| Data environments | Hybrid multicloud and SaaS data stores. |
| Unstructured data | Files prepared for vector databases and model training. |
Company Background
| Founded | 2019, by Rehan Jalil. |
|---|---|
| Headquarters | San Jose, California, United States. |
| Ownership | Acquired by Veeam Software, in a deal completed in December 2025 for a reported $1.725 billion in cash and stock; about 600 employees joined Veeam. |
| Leadership | Rehan Jalil, Founder, now President of Security and AI at Veeam. |
| Recognition | GigaOm DSPM report and Forrester Wave for Privacy Management (2025), and Frost & Sullivan recognition for DSPM. |
Note: This overview is compiled from Securiti’s publicly available information as of 4 November 2026. It is provided for information only. NHI Mgmt Group does not endorse any vendor, and nothing on this page represents the opinions of NHI Mgmt Group.