Information Security, Governance & Compliance Overview

1. Executive Summary

CaseFlow Automation Ltd operates LegalDocs-Assist, a SaaS platform that helps UK legal practitioners working in RTA (including credit hire), Employers’ & Public Liability, housing disrepair, and clinical negligence to analyse insurer and defendant correspondence, draft responses, and produce structured case documents — all supported by AI cross-referenced against a curated legal knowledge base.

Security and privacy are built into the platform's architecture, not bolted on. Our approach is grounded in data minimisation, privacy by design, and honest framing of what our controls achieve and where their limits lie.

2. About CaseFlow & Scope

Service Description

LegalDocs-Assist is a browser-based SaaS platform for UK legal practitioners across four practice areas: RTA (including credit hire), Employers’ & Public Liability, housing disrepair, and clinical negligence. Core features include:

• Witness Statement Generator: CPR Part 32-compliant draft statements from structured inputs
• Correspondence analysis: identifying insurer/defendant arguments and cited authorities
• AI-assisted reply generation, cross-referenced against curated case law
• Liability Assessment: indicative apportionment from accident statements against authorities
• Impecuniosity Assessment: 10-step financial ruleset applied to claimant statements and supporting documents
• Case Advice: structured strategic guidance on case posture and next steps
• Case Law Bible: curated, verified UK precedent library
• Medical Pagination (clinical negligence): combine, deduplicate and paginate multi-file medical records into a court-ready bundle
• Clinical Negligence Chronology: date-ordered chronology from medical records and correspondence
• Disrepair Chronology (housing disrepair): date-ordered chronology of disrepair events, defects and severity flags, exportable to Word/CSV
• Industry Resources: GTA protocol and rate tables, ABI guidance, Law Society and MoJ procedural rules, Road Traffic Act statutory references, and major hire-provider T&Cs

Service Boundary

Hosting Region

The platform is hosted in the European Union via managed cloud infrastructure. Data residency is EU-based.

3. Trust Model & Security Principles

• Privacy by Design & Default: Data minimisation is architectural. PDFs are processed locally except for the medical pagination feature (see below), PII is masked before AI processing, and retention is purpose-limited.
• Least Privilege: Row-Level Security (RLS) enforces per-company data isolation at the database level. Users can only access their own company's data.
• Defence in Depth: Controls operate at multiple layers: browser, network, application, database, and AI prompt level.
• Transparency: We use honest language about what our controls achieve. We say "attempts to mask" rather than "guarantees removal". We document limitations alongside capabilities.

4. Data Governance & Privacy (UK GDPR)

4.1 Controller / Processor Roles

Lawful basis: Contractual necessity for providing the Service; legitimate interest in providing efficient legal support tools.

4.2 Data Classification

4.3 Privacy-by-Design Data Handling

Layer 1: Browser‑side and server‑side text handling of source documents. Text‑based PDFs are read in the user's browser and only the extracted text is transmitted, for the drafting tools and for the Witness Statement document slots alike. Word and plain‑text documents submitted to the document slots are reduced to text on the server and masked before any AI processing. Three documented exceptions apply where an original file does reach the server: (i) scanned or image‑only documents, briefly processed so the text can be read at all; (ii) photographs and audio recordings submitted to the document slots, which the AI reads directly because there is no text to mask first; and (iii) the Medical Pagination tool (see its own section below). All exception paths run under Zero Data Retention terms, prompts and outputs are not stored by the AI provider, and the platform's automated deletion controls apply.

Layer 2: PII Masking Gateway. Before any text is sent to the AI model, it passes through a mandatory server-side masking gateway covering 16 verified categories: personal names (titled names always; bare / untitled names in high-precision contexts such as field labels, salutations and sign-offs), email addresses, UK phone numbers, National Insurance numbers, NHS numbers (Mod 11 validated), HMRC tax identifiers (Unique Taxpayer References and PAYE references), UK driving licence numbers, vehicle registration marks (VRMs), IBANs, credit and debit card numbers (Luhn-checked), sort codes, bank account numbers, dates of birth (in context), policy and claim references, and street addresses. Detected items are replaced with neutral placeholders such as [NAME_REDACTED], [NHS_REDACTED], [UTR_REDACTED] or [VRM_REDACTED]. An additional aggressive output-side re-scrub runs on AI responses to catch bare First-Last name pairs that slipped past the input gateway, with guards for case citations (X v Y) and known organisation names.

UK postcodes are deliberately preserved. Postcodes are material to BHR locality arguments in credit hire and to venue analysis in housing disrepair; masking them would degrade legal output. Two safeguards make this safe: (i) the AI provider's enterprise terms prohibit training on inputs or outputs, and (ii) an output-side scrubber (postcodeScrubber.ts) strips any postcode appearing in the AI response that was not present in the original input, preventing fabricated locality data.

The masking gateway is mandatory and a strong first layer, but it is pattern‑based and not a perfect filter. We do not claim full redaction or guaranteed coverage; users are asked to send only what the task needs. Every AI‑facing function that receives text invokes the masking gateway before the model call; there is no text path that bypasses it. Inputs that arrive as scans, photographs or audio cannot be masked before reading, because masking requires text. Those paths are documented exceptions protected by Zero Data Retention terms and automated deletion, and any structured fields they produce are masked again in later drafting steps. Each invocation logs the count and categories of items masked. Original values are never logged.

Where the AI runs and what happens to the output. AI drafting and generation happens on our server — that is where the model runs — under the Lovable AI Gateway's Zero Data Retention terms (the provider does not retain or train on the data). The generated output is produced on our server and then deleted shortly after it is returned to the user, not retained. We do not claim that nothing ever touches our servers; the AI output does, briefly.

Party names in the Witness Statement Generator. In the Witness Statement Generator, the party names entered on the form (claimant, defendant, witnesses) are passed to the model so the statement attributes evidence to the correct person. In the analysis tools, titled and labelled names are masked like any other identifier.

AI provider terms. The AI provider operates under the Lovable AI Gateway's Zero Data Retention terms, in force since March 2026: prompts and model responses are not retained by the provider and are not used to train any model.

Medical Pagination Feature

The medical pagination feature is the single deliberate exception to our local-only PDF processing principle. Source PDFs uploaded for this feature are briefly stored in a private, access-controlled storage bucket while the feature processes them. Source PDFs are deleted as soon as the pagination completes, whether successful or not. The output bundle PDF is available for you to download for up to one hour from creation. As soon as you successfully download the bundle, the file is removed from our storage. If for any reason it is not downloaded within an hour, it is automatically deleted by our scheduled cleanup. Our audit records retain the fact that a bundle was generated, but never the content itself.

4.4 Data Retention & Deletion

LegalDocs Assist is designed not to retain personal case data. Uploaded source documents and the outputs the tool generates (witness statements, paginated bundles, chronologies, timelines, advice, correspondence) are deleted shortly after they are produced or on session close, and a scheduled purge runs continuously as a backstop so case content is never retained beyond 24 hours. Controllers are expected to download or save their own copy of any output they need, and to re‑run the tool if needed. Medical‑bundle pagination files are deleted within roughly one hour of completion. Inactive login sessions expire automatically. The only data retained is the minimal account record needed to run the subscription; activity and audit logs are retained as stated elsewhere in this document.

Backups. Uploaded documents and generated bundles are not included in these backups. The database has standard disaster‑recovery backups, but because case content is deleted within 24 hours those backups hold essentially no personal case data, and once a record is deleted there is nothing to restore it from.

Special category (health) data. The Service routinely processes special‑category health data (medical records, injury, treatment) for clinical‑negligence and personal‑injury work. Safeguards: browser‑side processing of source documents, server‑side PII masking before any text reaches the AI, encryption in transit and at rest, and immediate deletion within 24 hours. As data controller, the firm is responsible for the Article 9 lawful basis.

Deletion semantics. Deletion on the platform is immediate and permanent. When a record or document is deleted it is removed from the live database and, where it has associated files, from storage. Deleted storage objects are not held in any backup and cannot be restored.

Account deletion. An individual user account can be deleted on request. The user's profile and account data are removed. Case content created under the controller's tenant remains under the controller's control until the controller deletes it or the contract ends.

Firm-level (tenant) erasure. On contract termination, or on a verified erasure request, we permanently delete the controller's tenant: all case content, witness statements, chronologies, correspondence, generated documents and the associated storage objects, together with the user accounts. This action runs only via a hardened admin path executed by CaseFlow Automation Ltd platform administrators — controllers cannot self-delete a tenant — and requires the tenant to be archived first as a reversible step, then permanently deleted from the archived list as a second gate. It is recorded in a tenant_deletion_audit row that holds only the fact of deletion, who performed it, when, and the row and object counts, never the deleted content itself. The only data retained is the minimal account and billing record required by law, and the Data Processing Agreement audit history, both stripped of unnecessary personal data. This is a contractual commitment honoured operationally, not an automated platform feature.

On termination. On contract termination the tenant is archived immediately; the archive remains reversible for thirty (30) days as a grace period, then permanently deleted from the archived list as a second gate. Tenant erasure is executed within thirty (30) days of contract termination unless the controller requests earlier execution. Statutory account and billing records are retained for the limitation period and then deleted.

4.5 Data Subject Rights

Under UK GDPR, data subjects have the rights of access, rectification, erasure, restriction, portability and objection.

Controller-held data (claimant records). For personal data about the controller's own clients and claimants, the controller fulfils data subject requests. CaseFlow Automation Ltd, as processor, supports the controller in fulfilling those requests, including by deleting or exporting the relevant records on the controller's instruction. The technical capability is in place: RLS-scoped queries scope reads and writes to the controller's tenant, and admin-initiated user and tenant deletion paths execute cascading erasure across the database and storage.

Processor-held account data. For account data CaseFlow Automation Ltd holds as controller (user credentials, usage logs), the data subject may exercise these rights directly by contacting info@caseflowautomation.co.uk. Data subjects also have the right to complain to the Information Commissioner's Office.

4.6 International Transfers

Platform data is hosted in the EU. Where AI model inference involves processing outside the UK/EEA, this occurs under the provider's enterprise data processing terms which include Standard Contractual Clauses (SCCs) and prohibit the use of input/output data for model training.

5. Security Architecture

5.1 Hosting & Infrastructure

• Hosted on managed cloud infrastructure with EU data residency
• TLS encryption for all data in transit
• AES-256 encryption for data at rest
• Managed database with automatic backups, point-in-time recovery, and encrypted backup storage
• Infrastructure managed by established cloud providers with SOC 2 Type II and ISO 27001 certifications

5.2 Application Security

• All AI interactions are mediated through server-side functions. Users never interact with the AI model directly.
• System prompts and knowledge base content are injected server-side; users cannot modify or view underlying instructions
• Input validation and sanitisation on all user-submitted data
• No API endpoint allows arbitrary prompts to the AI model
• Content Security Policy headers, HTTPS-only access

5.3 Network Security

• HTTPS (TLS) enforced for all connections
• API rate limiting on authentication and AI endpoints
• Server-side functions operate in isolated execution environments with no persistent state between invocations

6. Identity & Access Management

6.1 Authentication

6.2 Role-Based Access Control (RBAC)

Roles are stored in a dedicated user_roles table, separate from user profiles, and enforced via database-level security functions.

6.3 Data Isolation

Every database table containing client data enforces Row-Level Security (RLS) policies. These policies are evaluated at the database level on every query and cannot be bypassed by the application layer. A user from Company A cannot access, view, or modify data belonging to Company B, even if they manipulate API requests.

7. AI Governance & Model Risk Management

7.1 AI Use Cases & Human Oversight

AI is used exclusively for decision-support. It drafts, analyses, and suggests. It never makes legal decisions, sends correspondence, or takes autonomous action.

Every AI output is presented as a draft requiring human review. Users must explicitly accept a disclaimer acknowledging this before accessing AI features.

7.2 Anti-Hallucination Controls

7.3 Data Controls for AI

• PII masking before transmission: All text passes through the mandatory masking gateway before reaching the AI model
• No training on client data: Client correspondence and case details are never used to train or fine-tune AI models
• Prompt minimisation: System prompts include only the knowledge necessary for the specific task
• No persistent context: AI prompts are transient and are not stored or reused across sessions
• Server-side only: Users never interact with the AI model directly. All prompts are constructed and transmitted server-side.

7.4 Model Selection & Governance

• Models are selected centrally for their suitability for legal text analysis and are not configurable by end users
• AI model providers process data under enterprise data processing terms that prohibit training on input/output data
• Model changes are tested and validated before deployment

8. Monitoring, Logging & Incident Response

8.1 Logging & Audit Trail

8.2 Monitoring

• Server-side function execution is monitored via managed cloud logging
• Usage dashboards available to company managers (team activity) and platform administrators (aggregate metrics)
• Automated health checks on AI inference endpoints

8.3 Incident Response

In the event of a suspected security or AI safety incident:

1. Detect and Triage: Identify the scope and severity of the incident using available logs and monitoring
2. Contain: Affected AI features can be disabled immediately at the platform level. User sessions can be terminated. API keys can be rotated.
3. Investigate: Audit logs allow identification of affected outputs, users, and timeframes
4. Notify: Affected clients are notified with details of the issue and recommended actions. Regulatory notification (ICO) within 72 hours where required under UK GDPR Article 33.
5. Remediate: Root cause analysis conducted; controls updated and tested before re-enabling affected features
6. Review: Post-incident review to update procedures and controls

8.4 AI-Specific Incident Actions

• Identify event type (fabricated case law, data leakage in output, unexpected model behaviour)
• Disable affected AI feature(s) at platform level
• Review prompt and masking logs to assess exposure
• Update system prompts, knowledge base, or masking rules as required
• Validate fix before re-enabling

9. Business Continuity & Disaster Recovery

10. Third-Party Risk & Sub-Processors

CaseFlow uses a limited number of third-party services to deliver the platform:

All sub-processors operate under data processing agreements. Client notification will be provided for material changes to the sub-processor list.

11. Compliance & Control Mapping

11.1 Regulatory Alignment

11.2 Control Mapping (Against ISO 27001 Domains)

12. Shared Responsibility

13. Appendices

Appendix A: Related Documents

Appendix B: Glossary

Appendix C: Contact and Enquiries

For security-related enquiries, DPIA collaboration, or to request further technical detail: