VestraData scans your databases and file stores, returns field-level findings with confidence scores, and lets you anonymise in place or generate production-like test data — all inside your own infrastructure.
In a technical review, this is built live from one of your real sources.
Staging databases refreshed from production. Analytics environments with real customer records. Every one of these is a standing regulatory exposure — and the masking scripts meant to prevent it break on every schema change.
VestraData does one job thoroughly — it finds regulated data and produces governed, usable alternatives to it, with the audit trail to prove it.
Connect PostgreSQL, MySQL, Snowflake, S3, or SharePoint with a read-only credential. VestraData samples schemas and returns field-level findings — what was detected, how many rows, and at what confidence.
Apply masking and anonymisation directly where the data lives. Remove personal data from staging and analytics environments without rebuilding pipelines.
Extract referentially intact subsets and generate statistically faithful synthetic datasets. Engineering, QA, and ML teams work with data that behaves like production.
Every finding, decision, and transformation is written to a tamper-evident, hash-chained record. When a regulator asks what you found, you export the log.
Also in the platform: a data airlock for governed document sharing, an SDK/API for embedding detection in your own pipeline, and VestraShield — a companion browser tool that redacts sensitive content before it reaches external AI tools, available to evaluation customers.
Every deployment model keeps production data inside your boundary. There is no VestraData cloud that your data passes through.
Deploy into your own AWS, Azure, or GCP account. Your networking, your IAM, your storage. No production data touches vendor infrastructure.
Runs inside a private data centre or restricted network segment with no internet dependency at runtime. Offline licensing, no phone-home.
Run the detection and policy layer in-process inside your own product or pipeline when a standalone deployment is not the right fit.
The obligations differ by sector; the underlying problem doesn't.
SRA expects technical controls. A policy document alone won't satisfy it.
Read the briefHealthcare & NHSPatient data doesn't stop at the ward boundary. Your anonymisation controls have to cover every system that touches it.
Read the briefFinancial ServicesCardholder data in staging and analytics environments creates PCI scope that doesn't disappear without technical controls at the source.
Read the briefData MarketplacesEvery dataset you publish carries your reputation. Know what's in it first.
Read the briefML EngineeringTraining on production data creates regulatory exposure your model cards won't cover.
Read the briefDev & TestProduction data in staging is a GDPR incident waiting to happen.
Read the briefForty-five minutes, one read-only credential to a representative source, and you watch discovery and scanning happen in real time. No prepared screenshots, no sandbox with fabricated data.
Cambridge is home to one of Europe's densest concentrations of deep-tech and AI research — we're building alongside that ecosystem, not claiming it as our own track record. VestraData is working with a small number of organisations ahead of a wider release. You won't find customer logos or case studies here yet — which is exactly why our first conversation is a live scan of your real data rather than a pitch. Read more about the company, or email us directly — a founder replies, not a sales sequence.