MindLife UK Ltd is at the forefront of digital therapeutics, bridging the gap between clinical expertise and cutting-edge AI technology. We provide scalable, evidence-based solutions designed to enhance mental health, deliver clinically effective and cost-effective treatments at scale, and empower individuals to take control of their well-being.

1. Core Technology Platforms

Our solutions are powered by a proprietary ecosystem of AI-driven tools that personalise care and optimise clinical outcomes.

• Ai-Leap (Digital Development Platform): A robust platform that enables the rapid creation of interactive, responsive apps and websites. It converts traditional face-to-face interventions into engaging digital "lifeware."
• StratCare (AI Patient Stratification): Our intelligent triage system uses machine learning to analyse patient data and recommend the most effective treatment path—whether self-help, low-intensity, or high-intensity therapy.
• AiOracle (Measurement-Based Care): A predictive tool for clinicians that monitors patient progress in real-time, predicting recovery probabilities and alerting therapists when a patient may need additional support.
• BioView (Biomarker Analysis): Utilising standard mobile or computer cameras, BioView analyses facial changes and skin colour to track Heart Rate Variability (HRV) and emotional states, providing objective biofeedback to both users and clinicians.

2. Clinical & Professional Solutions

We partner with healthcare organisations, insurers, and clinicians to reduce waiting lists and improve the efficiency of mental health services.

• UpLift Remote Therapy: A next-generation remote therapy service combining human support with digital tools. Based on the "Unified Protocol" for transdiagnostic treatment, it offers:
  • Remote Group Therapy: Cost-effective, scalable sessions for people with similar conditions.
  • Personalised Skill Apps: Every participant receives a tailored app for daily practice between sessions.
• Blended Care Models: We provide tools that integrate seamlessly with existing clinical workflows, allowing therapists to treat more patients simultaneously while maintaining high standards of personalised care.
• Research & Data Insights: Our tools offer researchers access to large, anonymised datasets to better understand conditions like stress-related burnout and Disorders of Gut-Brain Interactions (DGBI).

3. Digital "Lifeware" & Self-Help

"Lifeware" is our term for therapeutic methods—cognitive, behavioural, and psychological—translated into motivating digital formats.

• Mental Health Apps: Highly effective interventions for common mental health disorders (anxiety, depression, OCD, PTSD and phobias).
• Well-being & Resilience: Designed for healthcare organisations to improve cognitive function, discover personal strengths, and prevent burnout among staff.

4. Biofeedback

Beyond software, MindLife develops inexpensive, high-precision sensors that track minute changes in the autonomic nervous system.

• Real-time Biofeedback: Sensors provide immediate feedback on how a user responds to specific thoughts or stimuli.
• Mind-Driven Games: Users can engage in therapeutic games driven by their emotional state, training the brain to regulate reactions without the need for manual input.

Delgadillo et al., (2022). Stratified Care vs Stepped Care for Depression. JAMA Psychiatry, 79;(2):101-108. [Link]

de Jong, K., et al. (2021). Using progress feedback to improve outcomes and reduce drop-out, treatment duration, and deterioration: A multilevel meta-analysis. Clinical Psychology Review, 102002. [Link]

Delgadillo, J., et al. (2017). Improving the efficiency of psychological treatment using outcome feedback technology. Behaviour Research and Therapy, 99, 89-97. [Link]

Delgadillo, J., et al (2018). Feedback-informed treatment versus usual psychological treatment for depression and anxiety: a multisite, open-label, cluster randomised controlled trial. The Lancet Psychiatry, 5(7), 564-572. [Link]

Delgadillo, J., et al. (2021). Cost-effectiveness of feedback-informed psychological treatment: Evidence from the IAPT-FIT trial. Behaviour Research and Therapy, 142, 103873. [Link]

Bone, C., et al. (2021). Dynamic prediction of psychological treatment outcomes: development and validation of a prediction model using routinely collected symptom data. The Lancet Digital Health, 3(4), e231-e240. [Link]

Delgadillo, J., et al. (2025). Implementation of a dynamic progress feedback technology in routine psychological care: a quasi-experimental, case-control study. (in preparation).