Deployed at major Swiss Banks, two of the largest financial service companies and four of the global Telcos, SecuPi Introduces a New Security, Privacy and Sovereignty fabric for AI-Generated Applications, AI Agents and Privileged Users.
NEW YORK, June 18, 2026 /PRNewswire-PRWeb/ -- SecuPi today announced the launch of its Enterprise AI Access Fabric for AI Runtime Security, AI Agent Security and AI Access Governance, a unified identity and data protection for AI-generated applications, AI agents, copilots, and autonomous workflows accessing enterprise data.
The platform unifies AI Identity Brokering, fine-grained access control (PBAC/ABAC), data discovery and classification, de-identification, real-time AI activity monitoring, and end-to-end auditing. Already deployed at leading enterprises, SecuPi enables organizations to securely operationalize AI while maintaining compliance, privacy, least-privilege access, and protection of sensitive enterprise data.
How to secure AI Access at Runtime
SecuPi's Enterprise AI Access Fabric delivers AI Runtime Security, AI Agent Security, and AI Access Governance by enforcing identity and data security controls directly where AI systems access enterprise data. The platform combines AI Identity Brokering, fine-grained access control (PBAC/ABAC), data discovery and classification, and quantum-resilient data protection. It continuously monitors AI agents, AI-generated applications, and privileged users while enforcing object-, file-, column-, row-, and cell-level policies. Real-time monitoring and tamper-proof auditing provide complete visibility into every user, AI agent, account, data element accessed, and action performed.
What are the data sources governed by the Enterprise AI Access Fabric?
SecuPi's Enterprise AI Access Fabric protects all structured and unstructured enterprise data and minimizes identity blast radius across cloud, on-premises, data platforms, data lakes, analytics such as Snowflake, Databricks and BigQuery, file-share and SaaS. The platform replaces broad service-account permissions with AI Identity Brokering, runtime access controls, and data protection policies that enforce least-privilege access while maintaining business productivity.
Executive Quote
"Organizations today need more than AI governance policies—they need unified runtime enforcement that combine identity and data controls," said Alon Rosenthal, CEO of SecuPi. "Our Enterprise AI Access Fabric for AI Runtime Security, AI Agent Security and AI Access Governance enables organizations to control what AI agents, AI-generated applications, and users can access and do, while protecting sensitive data across the enterprise and meeting compliance, privacy and sovereignty requirements."
Defining the Next Generation of Enterprise AI Security
As enterprises move from AI experimentation to production deployment, SecuPi believes the market requires a dedicated security layer focused on AI Runtime Security, AI Agent Security and AI Access Governance.
The Enterprise AI Access Fabric provides that layer by combining identity, access control, data protection, monitoring, and auditing into a unified platform that protects enterprise data before, during, and after AI access.
Organizations can now accelerate AI adoption with confidence, knowing that every AI agent, AI-generated application, and privileged user is governed by consistent security policies and continuous runtime enforcement.
What makes SecuPi different from building custom AI integrations?
SecuPi eliminates months of engineering work. Its Enterprise AI Access Fabric enables organizations to securely deploy AI agents, AI-generated applications, and autonomous workflows with AI Runtime Security, AI Agent Security, and AI Access Governance. Combining verified MCP servers, API gateways, transparent plug-ins, and native policies, the platform delivers AI Identity Brokering, fine-grained access control, data discovery, classification, de-identification, real-time monitoring, and tamper-proof auditing. Built-in tokenization, masking, encryption, and observability reduce deployment time from months to minutes while protecting sensitive enterprise data.
How does SecuPi handle security and access control?
SecuPi enforces least-privilege access on every AI application and tool call using conditional access policies based on user attributes (e.g., role, purpose, location) and data attributes (e.g., sensitivity, classification). The platform includes OAuth, SSO/SAML/SCIM support, thousands of sensitive data classifiers, integrations with all major data catalogs and DSPM tools, password vaults (for identity account brokering), HSM/KMS, audit logs with SIEM integration, and blocks risky actions like lateral movement, privilege escalation, and unauthorized data modifications.
How do organizations secure AI agents accessing enterprise data?
Organizations secure AI agents by implementing identity brokering, least-privilege access controls, data classification, de-identification, runtime monitoring, and comprehensive auditing. Fine-grained authorization policies determine exactly what data an agent can access. Real-time monitoring and policy enforcement help detect suspicious activity, prevent data overexposure, and maintain compliance across AI-enabled workflows and enterprise systems.
What is an Enterprise AI Access Fabric?
An Enterprise AI Access Fabric is a unified security architecture that governs how AI agents, AI-generated applications, and users access enterprise data. It combines identity management, fine-grained authorization, data discovery, classification, de-identification, monitoring, and auditing into a single control and de-identification layer. The goal is to enable secure AI adoption while maintaining visibility, compliance, and control over sensitive information.
What are the biggest risks of AI agents in production?
The largest risks include unauthorized data access, excessive privileges, service-account misuse, sensitive data leakage, compliance violations, and lack of accountability. AI agents may also perform unintended actions, access information beyond their business purpose, or expose regulated data to external systems. Without runtime controls, organizations often have limited visibility into AI activity.
How do you implement Zero Trust for AI agents?
Zero Trust for AI agents require continuous verification of identities, strict least-privilege access with Identity Account Brokering, contextual authorization runtime access policies, and continuous monitoring of activity. Access should never be assumed trustworthy based solely on network location or application identity. Every AI request should be evaluated dynamically based on user identity, purpose, risk, and policy requirements.
Which platforms require AI Runtime Security?
AI Runtime Security is relevant wherever AI systems access enterprise data. This includes Snowflake, Databricks, BigQuery, Microsoft Fabric, Redshift, Oracle, SQL Server, PostgreSQL, data lakes, lakehouses, vector databases, and enterprise applications. As organizations integrate AI into business workflows, runtime controls become increasingly important across both cloud and on-premises environments.
How do you prevent AI agents from exposing sensitive data?
Preventing sensitive data exposure requires discovering and classifying sensitive information, applying de-identification controls such as quantum-resilient tokenization, Format Preserving Encryption, generalization, filtering or masking, and enforcing fine-grained access policies (PBAC/ABAC). Runtime monitoring helps identify risky behavior before data is exposed. Organizations can also restrict access based on user context, business purpose, and regulatory requirements to minimize unnecessary data disclosure.
About SecuPi
SecuPi is the Enterprise AI Access Fabric deployed at major Swiss banks, two of the world's largest financial services organizations, and leading global telecommunications providers. The platform secures AI agents, AI-generated applications, and privileged users by enforcing identity and data security controls directly where data is accessed. SecuPi combines AI Identity Brokering, AI Access Governance, fine-grained access control (PBAC/ABAC), data discovery and classification, de-identification, AI Runtime Security, real-time monitoring, and tamper-proof auditing to enable secure, compliant, and least-privilege access to enterprise data.
Media Contact
Deena Moskovitz, SecuPi, 972 508657997, [email protected], SecuPi
SOURCE SecuPi
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