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Regulatory context

What your organisation is required to have in place.

These are the specific frameworks and obligations relevant to your sector, not a generic GDPR checklist. Each one has a direct implication for how you govern AI use and data handling.

SRA AI Guidance

Firms must have enforceable technical controls for AI use. A policy document alone does not meet the requirement.

GDPR Art. 30

Records of processing activities must include AI tool use where personal data is involved.

GDPR Art. 32

'Appropriate technical measures' means something enforceable. An AI usage policy without technical enforcement does not qualify.

COLP Personal Liability

The Compliance Officer for Legal Practice carries named individual regulatory risk, not just corporate risk.

Legal Professional Privilege

AI tools receiving privileged client communications create disclosure risk that only technical controls address.

ICO AI and Data Protection

Using AI tools to process client data triggers ICO guidance on lawful basis, data minimisation, and transparency. Documented risk assessments are expected, not just a policy.

Primary use cases

What your team gets from day one.

These are the specific workflows most organisations in your sector deploy first, in plain terms.

01
Prompt and document intercept before ChatGPT, Claude, and Copilot

Every prompt and file upload to any LLM is intercepted before it leaves your network. PII and privilege material is replaced with consistent surrogates. Real values are restored in the response. No real data reached the model.

02
Document management pre-clearance before AI use

Documents pulled from your DMS (iManage, NetDocuments, SharePoint, or any other system) into AI tools pass through VestraData's airlock automatically. A governed clean copy is produced before the document reaches any AI endpoint — no privilege risk, no manual review.

03
COLP-ready audit log for regulatory submissions

Every entity detected, every surrogate applied, every decision made: all written to a tamper-evident, hash-chained audit record. When the SRA asks what technical controls you have, you export the log.

04
Matter reference and client code anonymisation

Custom entity types like matter references, client codes, and internal identifiers are caught by the same zero-shot engine as PERSON and EMAIL. Configured once, applied consistently across every AI endpoint.

Where to start

Which product to deploy first, and why.

Both products share the same detection engine. Most organisations in your sector start with one before adding the other.

Lead product
VestraShield

The control layer between your people and every LLM endpoint. Transforms sensitive content in prompts before it reaches any AI model. Required to demonstrate technical enforcement to the SRA.

Complementary
VestraData

PII discovery across your document management system (iManage, NetDocuments, SharePoint, or others), practice management database, and file storage. Know what you hold before you govern what leaves.

Key capabilities

What's covered in a standard deployment.

Browser intercept (Chrome)

Covers ChatGPT, Claude.ai, Gemini, and Microsoft Copilot in the browser. Every prompt and file upload intercepted before it leaves the page. No endpoint agent required.

MCP proxy

Covers Claude Desktop, Cursor, and AI coding tools using the Model Context Protocol. The intercept plane most governance tools don't reach — if fee earners use AI in their IDE, this is where that traffic is caught.

HMAC-seeded surrogate consistency

The same client name becomes the same surrogate every time: across sessions, planes, and time. Cross-session entity consistency is what makes AI outputs coherent and complete.

Immutable audit log

Hash-chained, tamper-evident. GDPR Art. 30 compliant. Export directly to the SRA. Compliance evidence, not a log file.

Policy engine

Four actions per entity type: transform, block, warn, audit-only. Configured per application, per user group. No coding required. Deployed in your environment.

Air-gap deployment

Nothing reaches vendor infrastructure. ML models run in your environment. Required for firms with LPA obligations or client money segregation requirements.

DMS scanning

Field-level PII discovery across iManage, NetDocuments, SharePoint, and your practice management system. Confidence scores and row counts. No schema knowledge required upfront.

Data airlock for document handoffs

New documents arriving in monitored repositories trigger automatic pre-clearance. A governed clean copy is produced before the file reaches any partner, AI tool, or external system.

Matter file PII discovery

Find regulated data across matter repositories, client file stores, and email archives. Structured and unstructured sources in one review queue.

GDPR Art. 30 records of processing

Processing activity documentation generated automatically from scan findings. Evidence of what data you hold, where it lives, and what controls are in place.

Synthetic data for firm analytics

Anonymised matter and client data for business analytics, benchmarking, and internal reporting. Statistical distribution preserved. No real client data in analytics pipelines.

COLP-ready reporting

Exportable audit evidence package for SRA submissions and regulatory responses. Shows what was found, what controls were applied, and when.

Next step

Book a compliance review.

We connect to something real in your environment and you see actual findings. No slide decks. No fabricated data. Median time to first scan: under 4 hours from credentials.

For COLPs and compliance leads. We understand SRA timelines and what 'appropriate technical measures' requires.