Bluemetrix Expands SecureToken with Vaultless Tokenization and Zero-Trust Controls

SecureToken Vaultless Tokenization platform updates helping organisations deliver data-centric protection faster and securely.

CORK, IRELAND — April 2, 2026 — Amid accelerating cloud adoption, expanding AI workloads, and tightening regulatory requirements, Bluemetrix, the data security specialist behind SecureToken Vaultless Tokenization, has announced a major expansion of its SecureToken capabilities. The updates extend native data-centric protection across Cloudera, Snowflake, Teradata, AWS and all major database and cloud environments, built on three pillars: operational usability, zero-trust design, and API integration.

Using the NIST FF1 certified algorithm, SecureToken tokenizes sensitive fields by preserving data types and structures, so existing AI pipelines and analytics dashboards require no further modification to the way they ingest and process data. The Zero trust design model not only enforces authenticated, authorised access at every tokenization event, but also governs user behaviour into immutable profiles and security actions recorded to a tamper-proof audit trail. Moreover, SecureToken integrates with key management systems, SIEMs, and DLP/DSPM providers, removing lock-in to any single vendor.

"Vaultless Tokenization has always been the right answer for protecting sensitive data in production," said Leonardo Dias, Head of Architecture at Bluemetrix. "The problem was never the cryptography. It was the operating model built around it, vaults, proxies, and separate systems, you name it...that slowed teams down and multiplied risk. SecureToken removes that dominant model entirely. Protection is enforced at the data level, within the platforms data teams already use, without adding infrastructure or breaking the workloads that depend on that data."

According to a recent survey by the International Association of Privacy Professionals (IAPP), 78% of organisations reported data protection across AI workloads as their fastest-growing compliance gap — a challenge that legacy vault-based architectures were not designed to address.

"Every AI prompt containing sensitive data is a compliance risk most organisations have not yet fully accounted for," said Liam English, Chief Executive Officer at Bluemetrix. "SecureToken tokenizes PII before it reaches the model and de-tokenizes the response on return, with full audit coverage across Claude, GPT, Gemini, and LLaMA. Our agent-based tokenization via natural language is on track for Q2 2026."

A growing number of regulated enterprises across the financial services, healthcare, and government sectors are now using SecureToken to protect their entire data estate.

“Our customers are running AI on some of the most sensitive, confidential data in their industry. This is critical to accelerate data-driven decisions, as well as for the development of their own large language models for generative AI applications,” said Liam English, CEO at Bluemetrix. “We are still early in this journey. But we expect to see SecureToken become the way regulated industries protect data at the source, not the perimeter.”

SecureToken’s native User-Defined Functions (UDFs) execute tokenisation directly within the data processing layer in Cloudera, eliminating data movement, pipeline rewrite steps, or new infrastructure installation. Deployment of SecureToken can run on-premises, in the cloud, or in a hybrid environment via Kubernetes. Bluemetrix also provides dedicated onboarding, technical support, and ongoing training across all deployments, backed by its ISO 27001-certified security practice.

To learn more about SecureToken Vaultless Tokenization or to speak with the Bluemetrix team, visit www.bluemetrix.com/contact.