Usually a read-only database credential, file store, or bucket that is representative enough to answer whether the product fits your environment.
VestraData scans databases, files, and cloud storage for regulated data, then gives your team the controls to act. Runs entirely in your environment. Nothing leaves.
↑ Representative output, runs entirely inside your environment
Discovery, remediation, and proof across databases, files, and the AI tools your team uses every day.
Connect Postgres, MySQL, Snowflake, S3, and SharePoint. VestraCore samples schemas, scores fields by name, value, and context, and returns field-level findings with confidence scores and row counts.
Generate statistically faithful datasets for engineering, QA, and ML pipelines. Referential integrity is preserved. Distribution and correlation are matched. Exports go directly to staging DBs or object storage.
Watch repositories for new documents and datasets. When a match is found, a governed clean copy is produced ahead of time so partner handoffs and AI tooling never receive raw PII.
Intercept prompts and file uploads before they reach ChatGPT, Claude, or Copilot. Policy can warn, block, or transform without treating every employee as a privacy expert.
The CLI outputs field-level findings, row counts, and confidence scores. Every finding is written to a tamper-evident audit record before the session ends.
Every VestraData workflow follows the same sequence, from credential to evidence, regardless of data source or deployment model.
Three models. No vendor lock-in. No requirement to move data to assess it.
Deploy into your own AWS, Azure, or GCP account. Your networking, your IAM, your storage. No production data routed to vendor infrastructure.
Run inside a private data centre or restricted network segment. No internet dependency at runtime. For teams where operational data egress is ruled out by policy.
Embed the detection and policy layer directly into an existing pipeline or product when a standalone deployment is not the right fit.
VestraData deploys into environments where data residency, auditability, and access controls are non-negotiable, not optional extras.
Patient data stores, air-gapped deployments, DSPT + HIPAA coverage for NHS and private health systems.
PCI-DSS scope reduction, synthetic data for ML pipelines, LDAP/SAML auth for banks and insurers.
Controlled document sharing, AI DLP for client privilege materials, audit trail for law and accounting.
Scan inbound datasets before publication. Multi-tenant isolation with SDK-first integration.
Eliminate brittle hand-built masking scripts. Statistically faithful synthetic subsets for staging and QA.
Training and evaluation datasets that preserve distribution and correlation without accessing live data.
We are working with a small number of design partners in regulated industries, organisations with a real privacy, compliance, or data-governance problem and a team willing to work closely with us to solve it well.
Design partners get hands-on support from the team, early access to new capabilities, and a shorter loop from feedback to shipped product. Terms are structured for an early partnership and a defined pilot scope. If you want to be a public reference later, we welcome it, but we will never ask.
Apply as a design partner →Not a slide deck. Not a sandboxed environment with fabricated data. We connect to something real in your organisation and you see actual findings.
After the session, you should know whether the deployment model works, whether the first workflow is meaningful, and whether a pilot is justified.
Median time to first scan: under 4 hours from credentials.