We are a specialised team of AI engineers, clinical informaticists, and financial technology experts with deep domain expertise in building and deploying AI for regulated industries. We transform state-of-the-art foundation models into compliant, auditable, production-grade solutions that meet HIPAA, FCA, SOC 2, and GDPR standards — bridging the gap between cutting-edge AI research and the rigorous demands of healthcare and financial regulation. Based in Cambridge, UK, at the intersection of world-class AI research and regulated-industry deployment.
To bridge the gap between cutting-edge AI research and regulated-industry deployment. While foundation models like GPT-4, Llama 3, and Mistral have transformed what AI can do, deploying these capabilities in healthcare and financial services requires specialised expertise in compliance, validation, and governance. We make that transition seamless — transforming complex models into compliant, auditable solutions that earn trust through evidence, transparency, and rigorous clinical and financial validation.
Compliance-first. Evidence-based. Transparent. Every model we deploy is backed by clinical validation against established medical benchmarks, financial back-testing against historical datasets, and immutable regulatory audit trails. We prioritise patient safety and financial integrity above speed — because in regulated industries, trust is earned through rigour, not promises. We believe AI should augment human expertise, not replace human judgement.
Founded by veterans from NHS health technology programmes, tier-1 investment banks, and leading AI research institutions including Cambridge's Machine Learning Group. Our team combines deep expertise in clinical informatics, quantitative finance, regulatory compliance, and production ML engineering — with collective experience across 50+ regulatory audits, 200+ model deployments, and healthcare and financial systems serving millions of users.
Specialized capabilities spanning healthcare, financial services, and regulated AI deployment — from clinical validation to compliance audit trails.
Clinical text analysis using domain-adapted transformer models (BiomedBERT, ClinicalBERT, Med-PaLM architectures), diagnostic decision support, and seamless EHR integration via FHIR and HL7 APIs. Deep expertise in medical terminology systems (SNOMED CT, ICD-10, LOINC), clinical documentation workflows, and building AI systems that augment clinical decision-making with evidence-based rigour and retrieval-augmented generation.
Graph neural network-based fraud detection, credit scoring using gradient-boosted ensembles and deep learning, anti-money laundering (AML) systems, and real-time transaction monitoring with sub-40ms latency. Production experience with regulatory reporting under Basel III, IFRS 9, MiFID II, and FCA Consumer Duty frameworks, plus continuous model validation in live financial systems.
HIPAA, FCA, SOC 2, GDPR, and EU AI Act compliance expertise. We build immutable audit trails, implement automated fairness testing across protected characteristics, maintain model documentation to FDA SaMD standards, and ensure every AI decision is explainable and defensible under regulatory scrutiny — with over 50 audits passed across healthcare and financial services.
Expert fine-tuning of open-source foundation models (Llama 3, Mistral, Phi, Gemma) and domain-specific models (BioGPT, FinGPT) using LoRA, QLoRA, and full-parameter training. We achieve domain-expert performance on regulated tasks while keeping models compact enough for on-premise deployment in air-gapped healthcare and financial environments.
End-to-end EHR data pipelines with FHIR R4 and HL7v2 integration, Safe Harbor and Expert Determination de-identification protocols, medical imaging workflows (DICOM), and synthetic data generation with differential privacy guarantees. Secure data handling that maintains HIPAA compliance while enabling robust AI model training and validation at scale.
Kubernetes-orchestrated deployment pipelines with encrypted inference, zero-trust security architecture, immutable audit logging, and automated model governance. Model registries with approval gates, A/B testing frameworks, canary deployments, and continuous monitoring for drift, bias, and performance degradation — all designed for healthcare and financial compliance requirements.
Federated learning infrastructure that enables collaborative model training across hospital networks and banking consortia without sharing sensitive data. Combined with differential privacy, secure multi-party computation, and homomorphic encryption techniques to maintain strict data sovereignty while improving model accuracy across institutions.
Feasibility assessments, regulatory compliance roadmapping, build-vs-buy analysis, and AI maturity evaluations for healthcare and financial applications. We help clinical and financial leadership teams make informed decisions grounded in regulatory reality, clinical evidence, and a clear understanding of what today's AI can — and cannot — reliably deliver.
The AI industry moves fast — but regulated industries require measured, evidence-based adoption. Here's how we navigate that tension.
We don't bolt compliance onto finished models — we architect it in from day one. Every data pipeline, training run, and deployment decision is designed with HIPAA, FCA, SOC 2, and GDPR requirements as first-class engineering constraints. This compliance-first approach means our models are audit-ready from the moment they reach production, not months later after expensive remediation.
We validate every model against established benchmarks and real-world clinical or financial datasets before deployment. Our evaluation frameworks measure what matters in regulated contexts — not just accuracy, but fairness across demographic groups, calibration quality, hallucination rates, and performance under distribution shift. We publish internal evaluation reports that would withstand regulatory scrutiny.
We design AI systems that augment human expertise, not replace human judgement. In clinical settings, our models provide evidence-based recommendations that clinicians can accept, modify, or override. In financial services, our risk models surface insights and explanations that empower analysts and compliance officers to make better-informed decisions with full transparency.
Regulated AI is never "done." We build monitoring and feedback loops that track model performance, detect drift, and trigger retraining — all within governance frameworks that maintain audit trails. Our models improve over time through carefully controlled learning cycles that preserve compliance posture while adapting to evolving clinical guidelines, regulatory changes, and new fraud patterns.
Measurable outcomes from our AI deployments across healthcare and financial services.
Our clinical AI models are deployed across NHS trusts and private healthcare networks, delivering measurable improvements in diagnostic accuracy, clinician efficiency, and patient outcomes. From automated medical coding to predictive readmission models, our healthcare AI drives real clinical impact.
Our financial AI systems serve retail banks, investment firms, and fintech platforms across the UK and Europe. From fraud detection to credit risk scoring, our models identify threats that rule-based systems miss while maintaining full regulatory compliance and explainability.
Situated in one of the world's leading centres for AI research, biomedical science, and financial technology. Our Cambridge location places us at the heart of a vibrant ecosystem that includes world-class university research groups, NHS innovation hubs, and a thriving cluster of healthtech and fintech companies. This unique environment gives us access to exceptional talent and keeps us connected to the latest advances in clinical AI, computational finance, and responsible AI governance.
We'd love to learn about your healthcare or financial AI challenges and explore how we can help.
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