Securing Data and Governing AI at Scale
Author: Max Gilfedder
Release Date: 20/11/2025
As organisations look to unlock the potential of AI while meeting increasing compliance and data protection obligations, many are faced with the challenge of managing data sprawl and identifying sensitive information, especially in unstructured formats across cloud environments. Securiti offers a platform to address these challenges, enabling customers to secure their data and govern AI use at scale.
How Securiti Unlocks AI Potential
The Securiti platform leverages AI to identify and manage sensitive data wherever it resides, from SharePoint to OneDrive, across on-prem and multi-cloud environments. This enables actions such as quarantining, labeling files with classifications (e.g. using Microsoft Information Protection and/or Google Labelling), and applying additional metadata such as ‘Confidential’, ‘PII’, ‘First Name’ or ‘Last Name’. These labels and tags can be picked up by downstream tools such as DLP solutions, simplifying policy management, data retention schedules and enforcement policies.
Securiti’s approach allows organisations to unify data classification across different data stores, not just those within Microsoft’s ecosystem. This is especially useful for organisations using services like AWS S3 or GCP, where traditional tools like Microsoft Purview may have limited reach. By applying consistent classification and protection regardless of the data store, Securiti helps improve both visibility and control over sensitive information.
Unstructured data, (which may account for as much as 80-90% of enterprise data), presents significant challenges in terms of discovery, classification, access control, and maintaining data relevance. Securiti’s ability to connect to major data repositories and apply AI-driven classification enables organisations to gain clarity and control over their unstructured data estate.
Maintaining data lineage is also critical. In AI use cases, unstructured data that has been vectorised and used in models or automation can become orphaned, potentially resurfacing in ways that expose sensitive content. Securiti helps track data usage across pipelines, minimising the risk of unintentional disclosure and improving visibility into how data is being used.
On the compliance front, the platform includes a dedicated compliance module aligned to frameworks such as EU AI Act and UK AI legislation. This module continuously evaluates configurations in environments like AWS and Azure, providing automated attestation and real-time dashboards. It also supports compliance project mapping to eliminate duplicate effort, linking requirements across different frameworks where overlap exists.
To support secure AI deployment the platform includes the “GenCore” module. This enables safe ingestion of data into AI systems by preserving access controls, for example only users with permission to view sensitive files can retrieve related AI outputs. It also supports data sanitisation by masking sensitive fields before vectorisation, allowing data utility without compromising privacy.
Additional protection is offered through LLM firewalls that operate at key stages of the AI lifecycle, including prompt handling, retrieval and response. These firewalls can block prompt injection, unsafe queries and other malicious inputs. Organisations can customise these controls to meet their specific security and governance requirements.
To find out more about how Securiti supports securing data and governing AI at scale, you can watch our webinar on the topic. Alternatively, to find out more about Securiti’s capabilities in general, you can do so by visiting our Securiti partner page here!