Sentra launches AI data readiness platform for enterprises

Sentra has launched a platform for continuous AI data readiness and governance, aimed at enterprises managing sensitive data across cloud, SaaS and AI environments.

The launch addresses a problem many companies face as they expand their use of AI systems without a clear view of the data those systems can access. The platform is designed to discover, classify and govern sensitive information, while mapping which users, service accounts and AI identities can reach it.

Businesses have poured spending into AI models, computing infrastructure and governance policies, but data oversight has often lagged. That gap has become more acute as companies move beyond assistant-style tools to agentic AI systems that can traverse datasets, call application programming interfaces and act with inherited permissions.

In that environment, stale records, excessive permissions and poorly classified files can shift from dormant issues to active sources of exposure. Security and compliance teams are increasingly being asked to determine what sensitive data exists, where it resides and whether AI systems should be allowed to use it.

Research cited by Sentra highlights the pressure. Gartner has predicted that 60% of AI projects will be abandoned through 2026 because the data is not AI-ready.

Risk focus

Sentra said the platform is built around four areas of concern for organisations deploying AI: limited visibility into AI-accessible data, the spread of redundant or obsolete sensitive information, excessive permissions granted to users and machine identities, and the use of data in AI workflows without proper governance.

Its software continuously scans cloud storage, SaaS applications, data warehouses, collaboration tools and AI environments to identify regulated and proprietary data. It also flags redundant, obsolete and unnecessary information that may increase exposure and operating costs as more enterprise data is fed into AI systems.

Another element is identity and access mapping. The platform links sensitive data to the human users, groups, service principals and AI agents that can access it, helping organisations apply least-privilege controls based on data sensitivity and business context.

It can also send classification and policy signals to existing data loss prevention, identity and access management, AI gateway and cloud-native controls. The goal is to stop sensitive data from being pulled into copilots, retrieval-augmented generation pipelines, knowledge bases or automated workflows without suitable checks.

Core functions

Sentra said the platform offers five main functions: a classified inventory of sensitive data across cloud, SaaS, collaboration, data warehouse and AI environments; tools to identify unnecessary or overexposed information; governance that maps access rights across people and machine identities; automated remediation through existing security controls; and compliance support with evidence for regulations including GDPR, HIPAA, CCPA and the EU AI Act.

The system covers several major AI and data platforms, including AWS Bedrock, Azure OpenAI, Google Vertex AI, Snowflake Cortex and Microsoft 365 Copilot, according to the company.

Sentra also emphasised how customer data is handled. The platform operates within the customer's own environment using an agentless architecture, so sensitive data is not copied out for processing. Instead, metadata such as classification results, risk findings and access relationships is shared with the platform.

This model is intended to address data residency, privacy and compliance requirements while still giving security teams a current view of changing environments. It also reflects broader customer concern about where enterprise data is processed when third-party AI and security tools are introduced.

The product is available across AWS, Azure and Google Cloud environments. Its launch comes as companies seek ways to connect AI adoption, security controls and compliance obligations without slowing deployment.

"AI adoption has exposed a data readiness gap inside the enterprise," said Yair Cohen, Co-Founder and VP Product, Sentra.

"Organisations have invested in AI infrastructure and governance frameworks, but many still lack a current understanding of what sensitive data AI can reach. Sentra provides this missing data readiness layer and gives teams the foundation they need to govern AI data access, reduce exposure and keep pace as agentic AI expands," Cohen said.