Secure AI & RAG Systems

Proven Secure AI at Production Scale

Map My Tracks handles deeply personal data: GPS tracks revealing home addresses, health metrics showing medical conditions, workout patterns indicating daily routines. Processing this data through AI requires absolute security. We built Activity Insights to maintain complete data sovereignty:

Private data processing: User information never enters external AI training sets. We implement RAG architectures where queries access private data temporarily without persistence.

GDPR compliance at scale: 1 million users across 190+ countries, each with data protection rights we honour automatically. Deletion requests propagate through all systems including AI components.

Secure integration architecture: AI features access user data through controlled interfaces with audit logging, access controls, and encryption at every layer.

This production experience handling sensitive data at scale differentiates us from consultancies demonstrating concepts. We understand enterprise security requirements because we have built systems where security failures have consequences.

What We Build: Secure AI Implementations

RAG (Retrieval-Augmented Generation) Systems

AI accessing your documents, databases, and knowledge bases without sending data to external models for training. We implement vector databases storing your content securely, retrieval systems finding relevant information, and LLM integration maintaining data boundaries. The same approach Activity Insights uses accessing user workout history: data retrieved temporarily, processed securely, never persisted externally.

Private LLM Deployments

On-premise or private cloud AI models running entirely within your infrastructure. We handle model selection, deployment architecture, scaling configuration, and integration with your existing systems. Built using the security principles proven across NHS projects requiring complete data isolation.

Secure AI APIs

Controlled interfaces allowing AI capabilities whilst maintaining security boundaries. We implement authentication systems, rate limiting, audit logging, and encryption protecting your data throughout the AI workflow. The same API security standards applied connecting to every major UK bank for My Lost Account.

Hybrid AI Architectures

Systems combining public AI models for general capabilities with private systems for sensitive data. We design the boundaries determining what data stays internal, implement the secure interfaces, and create monitoring ensuring compliance. This architectural approach balances capability with security.

The RAG Architecture Explained

Retrieval-Augmented Generation solves a fundamental problem: how to give AI access to your private data without exposing it to external training.

Traditional AI risk: Sending your documents to ChatGPT or similar services means your data potentially enters their training sets. Even with assurances, you lose control.

RAG solution: Your data stays in your database. When someone asks a question, the system:

1. Searches your private documents for relevant information
2. Sends only that specific, temporary context to the AI
3. Gets the AI's response based on your data
4. Discards the temporary context
5. Never sends your data for model training

We implemented this architecture for Activity Insights. User workout data stays in our databases. When generating coaching insights, we retrieve relevant workout history temporarily, the AI generates personalised feedback, and no user data enters external training sets.

Industry Applications: Proven Security Implementations

Healthcare & Life Sciences

NHS projects taught us patient data protection, audit trail requirements, and compliance frameworks. A secure AI diagnostic system needs patient data access without external exposure, explainable decision-making for clinical safety, comprehensive audit logging for regulatory compliance, and architecture meeting NHS DSP Toolkit standards. We build healthcare AI because we understand healthcare security requirements.

Financial Services

My Lost Account connected to every major UK bank, demonstrating capability handling financial data with appropriate security controls. A secure AI financial advisor needs customer data isolation, transaction analysis without data leakage, regulatory compliance (FCA, GDPR), and integration with existing banking security infrastructure. We implement financial AI using approaches proven handling actual banking data.

Legal & Professional Services

Law firms and consultancies need AI accessing client documents whilst maintaining privilege and confidentiality. A secure document analysis system requires client data separation, privilege protection mechanisms, audit logging for compliance, and certainty that client information never enters external training sets. We build these systems understanding professional confidentiality requirements.

Manufacturing & Industrial

Production data, supply chain information, and process documentation represent competitive advantages that cannot be exposed. A secure AI operations system needs proprietary data protection, integration with industrial systems, on-premise deployment options, and architecture maintaining complete data sovereignty. We implement industrial AI using security principles proven across enterprise deployments.

Enterprise & Corporate

Large organisations need AI accessing internal knowledge bases, customer records, and strategic documents without security risks. A secure enterprise AI platform requires employee data protection, customer information security, intellectual property protection, and integration with existing corporate security infrastructure. We build enterprise AI meeting the security standards proven across our NHS and banking work.

How We Build Secure AI Systems: Production-Proven Process

Security-First Discovery (2-4 weeks)

We start by mapping your data landscape: what data exists, where it lives, who can access it, and what regulations apply. This security-focused discovery uses the same rigorous approach we applied before building NHS systems where patient data protection is non-negotiable. We document your security requirements, identify data sovereignty constraints, and design architecture maintaining compliance.

Private Infrastructure Design (2-3 weeks)

We design the complete secure architecture: private vector databases, on-premise or private cloud deployment, secure API boundaries, and integration with your existing security infrastructure. Having built Map My Tracks to handle sensitive location and health data for 1 million users, we understand what secure AI architecture requires at scale.

RAG Implementation (6-12 weeks)

We build the Retrieval-Augmented Generation system: document ingestion maintaining security, vector database implementation with access controls, retrieval systems respecting permissions, and LLM integration preventing data leakage. Every component implements the security principles proven across NHS and banking projects.

Security Validation (2-4 weeks)

We test the security boundaries: penetration testing on API interfaces, data leakage prevention verification, access control validation, and audit logging confirmation. This testing phase uses approaches developed building systems for NHS (DSP Toolkit compliance) and banking clients (FCA requirements).

Deployment & Monitoring

We deploy to production with comprehensive monitoring: data access logging, security event detection, compliance reporting, and performance monitoring. The same operational monitoring approach keeping Map My Tracks running reliably for 1 million users applies to your secure AI deployment.

What You Get: Production-Grade Secure AI

✓ RAG system maintaining complete data sovereignty using architecture proven with NHS and banking clients
✓ Private vector database implemented with security controls and access logging
✓ Secure LLM integration preventing data leakage through tested boundaries
✓ Audit logging meeting compliance requirements proven across regulated industries
✓ Data encryption (in transit and at rest) using standards required by NHS DSP Toolkit
✓ Access controls implementing role-based permissions at every layer
✓ Compliance documentation from a team meeting NHS, banking, and GDPR requirements
✓ Ongoing security support from developers maintaining production systems for 20+ years

Why This Matters: Data Sovereignty is Non-Negotiable

Most AI agencies can demonstrate impressive capabilities using public APIs. Few can demonstrate secure implementations handling sensitive data at scale.

We understand regulatory requirements. Building NHS systems meant meeting DSP Toolkit standards, implementing GDPR compliance, and creating audit trails satisfying regulators. Your secure AI gets the same rigorous compliance approach.

We have handled sensitive data at scale. Map My Tracks proves we can process private information (location data, health metrics) for 1 million users whilst maintaining security. My Lost Account proves we can integrate with major banks handling financial data appropriately.

We implement real data sovereignty. Our RAG architectures are not theoretical. We built Activity Insights using these principles: user data stays in our databases, AI accesses information temporarily, nothing enters external training sets.

We know where security fails. 20 years building production systems taught us about authentication bypass attempts, API abuse patterns, data exfiltration risks, and all the security concerns that only emerge at scale. Your system benefits from this hard-won operational knowledge.

Our Background: 20 Years Handling Sensitive Data

NHS projects: Patient data systems, DSP Toolkit compliance, GDPR implementation, comprehensive audit logging
Banking systems: My Lost Account connecting to every major UK bank, financial data security, FCA compliance
Map My Tracks: 1M+ users trusting us with location data, health metrics, workout history across 190 countries
Team Sky (2010-2015): Professional athlete tracking data, performance metrics, location privacy
Enterprise clients: 20+ years implementing security controls for corporate data, customer records, intellectual property

This background means we build secure systems, not security theatre. When you work with Tinderhouse, you work with a team that has spent two decades proving we can be trusted with sensitive data.