Consultancy Services
We help digital health companies build, validate, and scale AI that works — safely, compliantly, and commercially.
- Structured, expert-led stress testing of your AI agent or assistant
- We probe for safety failures, bias, edge cases, and regulatory blind spots
- Covers both LLM-based and deterministic system components
A detailed risk report with prioritised findings and a clear remediation roadmap.
- End-to-end design, build, and validation of your AI agent
- We handle the complexity so your team stays focused on their priorities
- Built to meet regulatory and clinical requirements from day one
- Uses both LLM and deterministic approaches depending on what the problem needs
A fully tested, deployment-ready AI agent with supporting documentation.
- Structured review of your acquisition, onboarding, and retention funnel
- We identify where AI can improve conversion, reduce churn, and increase lifetime value
- Analyse behavioural drop-off points, switching patterns, and revenue leakage
Quantified impact estimates, prioritised use cases, and a roadmap linking AI interventions to CAC, AOV, LTV, and margin improvement.
- We take your concepts and quickly turn them into functional prototypes
- Ideal for testing new ideas with real users before committing to full development
- Agile, low-overhead process designed to minimise disruption to your team
A working prototype you can demo, test, and iterate on — fast.
- Design governance frameworks for AI systems in regulated health environments
- Aligned with MHRA, CQC, EU AI Act, and international best practice
- Covers monitoring layers, escalation pathways, audit documentation, and risk classification
A governance blueprint, oversight roles and responsibilities map, and board-ready documentation pack.
- Rapid, focused engagement to diagnose and fix retention problems
- We define behavioural segments, adaptive messaging, and trigger thresholds
- Pilot design with measurable performance metrics built in from the start
An implementation blueprint for AI-driven retention, including measurement frameworks to reduce churn and strengthen loyalty.
- Map current prescriber and customer service workflows to find high-friction tasks
- Design AI co-pilot or automation layers that reduce manual load while maintaining safety
- Covers QA automation, tone support systems, and performance monitoring
A prioritised automation roadmap with implementation plan and safety guardrails.
- Board and executive advisory on AI strategy, governance, and implementation
- Support for companies undergoing due diligence for investment, partnership, or acquisition
- Practical, hands-on guidance — not slide decks that sit on a shelf
Clear strategic direction, a governance framework, and confidence in your AI decisions.
- Bespoke research in support of your business and clinical objectives
- Designed to be cost-effective and commercially relevant, not just academically rigorous
- Includes user and stakeholder research to understand real-world perceptions of AI
Credible research outputs — publications, white papers, or internal evidence packs — that support your strategic goals.
- Develop behavioural profiling models to segment users by motivation, barriers, and risk factors
- Translate profiles into adaptive AI pathways — personalised tone, content, cadence, and escalation
- Outputs include segmentation framework, decision architecture, and integration plan
An AI personalisation engine grounded in behavioural science, ready to integrate into your product.
