Compliance-ready, production-grade AI for medical diagnosis, clinical workflows, financial risk assessment, and fraud detection. We build audited AI models that meet HIPAA, FCA, SOC 2, and GDPR standards — from model training through deployment.
Specialized AI models engineered for compliance, clinical validation, and regulatory audit requirements across healthcare and financial services. Leveraging the latest advances in transformer architectures, retrieval-augmented generation, and multi-modal AI.
Medical NLP powered by domain-adapted large language models for diagnostic support, clinical workflow optimisation, and EHR integration. Our models leverage the latest advances in BiomedBERT, Med-PaLM architectures, and retrieval-augmented generation for evidence-based clinical decision support with FDA-aligned validation protocols.
Real-time risk scoring models, graph neural network-based fraud detection systems, and algorithmic trading compliance engines. We deploy state-of-the-art anomaly detection using transformer-based sequence models and federated learning to protect sensitive transaction data while maintaining FCA-compliant audit trails.
HIPAA/SOC2/FCA-compliant deployment infrastructure with automated model governance, continuous bias monitoring, SHAP-based explainability dashboards, and real-time drift detection. Built on Kubernetes with zero-trust security architecture and immutable audit logging for regulatory inspections.
We stay at the forefront of AI research to bring cutting-edge capabilities into regulated environments — safely and compliantly.
We fine-tune state-of-the-art foundation models — including Llama 3, Mistral, and domain-specific architectures like BioGPT and FinGPT — for regulated use cases. Our LoRA and QLoRA fine-tuning pipelines achieve domain-expert performance while keeping models compact enough for on-premise deployment in air-gapped healthcare and financial environments.
Retrieval-Augmented Generation eliminates hallucination in high-stakes environments. Our clinical RAG systems connect LLMs to verified medical literature, formularies, and treatment guidelines. In finance, RAG pipelines ground AI responses in regulatory documentation, case law, and compliance databases — ensuring every recommendation has a traceable evidence source.
We combine text, imaging, and structured data for richer AI models. In healthcare, this means integrating radiology images with clinical notes and lab results for comprehensive diagnostic support. In finance, multi-modal models analyse transaction data alongside communication metadata, geographic signals, and behavioural patterns for superior fraud detection.
Train powerful models across institutions without sharing sensitive patient or financial data. Our federated learning infrastructure enables collaborative model training across hospital networks and banking consortia — improving model accuracy while maintaining strict data sovereignty and regulatory compliance at every node.
A systematic, compliance-first approach to building AI that works reliably in production — designed for the unique demands of healthcare and financial regulation.
We begin every engagement with a thorough compliance audit. We evaluate HIPAA, FCA, SOC 2, and GDPR requirements alongside your data governance frameworks, identify sensitive data flows, and establish the audit-readiness baseline. We also assess data quality, volume, and labelling maturity to de-risk the model development process early.
Build initial models with compliance-first architecture. We select base models (Llama, Mistral, or domain-specific architectures) and configure fine-tuning pipelines with privacy-preserving techniques including differential privacy and federated learning. Clinical prototypes are validated against established medical benchmarks; financial prototypes against historical transaction datasets.
Advanced fine-tuning with LoRA/QLoRA, reinforcement learning from human feedback (RLHF), and domain expert evaluation. We build custom evals suites that measure clinical accuracy, hallucination rates, bias across demographic groups, and regulatory KPIs. Every model iteration is benchmarked against previous versions and industry baselines.
Kubernetes-orchestrated deployment with encrypted inference, immutable audit logs, automated model versioning, and real-time compliance dashboards. We configure monitoring for data drift, concept drift, and fairness metrics with automated alerting and retraining triggers — all accessible to regulators on demand.
Real outcomes from our production deployments across healthcare and financial services.
AI is revolutionising clinical care — from early disease detection to personalised treatment pathways. The global healthcare AI market is projected to reach $188 billion by 2030, driven by the urgent need for diagnostic accuracy, clinician workflow efficiency, and population health management. Our clinical AI models are deployed across NHS trusts and private healthcare networks, delivering measurable improvements in patient outcomes.
Financial institutions face an estimated $2 trillion in annual fraud losses globally, alongside mounting regulatory pressure for algorithmic transparency. Our financial AI systems detect sophisticated fraud patterns that rule-based systems miss, reduce false positive rates by up to 70%, and generate audit-ready explainability reports for every flagged transaction. We serve retail banks, investment firms, and fintech platforms across the UK and Europe.
Let's discuss how we can build compliant, production-grade AI models tailored to healthcare and financial sector requirements.
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