The enemy is the waiting list. One of the biggest reasons it exists is that clinicians spend hours turning messy case evidence into high-stakes reports.
Generated with AI - please review before finalizing
In the UK alone, the ADHD and autism waiting list stands at 800,000 and growing - projected to reach 1 million within two years. Delayed diagnosis means delayed access to support. Every week on a waiting list is a week without the help someone needs.
Throughput stays constrained, quality management costs grow, and contract performance becomes harder to sustain.
Reports consume nights, weekends, and emotional energy. The burden is personal, not abstract.
Delayed access to the support they need increases risk of poor outcomes, mental health crises, and unmet need.
Delayed or denied care creates wider educational, health, employment, and societal consequences.
Clinicians aren't writing from a single conversation. They're synthesising up to 20 messy, multi-source documents into one high-stakes diagnostic report. That process is where the system breaks down.
Interviews, developmental histories, questionnaires, school input, GP letters, therapist notes, cognitive assessments and more.
Highly trained clinical time consumed by synthesis and write-up rather than patient-facing work.
Weak, inconsistent, or poorly evidenced reports get queried or rejected - creating downstream risk for clinics, clinicians, and patients.
Different clinicians write differently. More growth means more QA overhead just to keep reports defensible.
Report writing spills into evenings and weekends, contributes to burnout, and consumes the time clinicians need for recovery or other patient work. The burden is emotional and professional, not just administrative.
Without changing the workflow your clinic already uses.
Developmental histories, questionnaires, school input, referral information, assessment notes and related records.
Classifies material, builds a structured draft aligned to your clinic's format using AI designed for diagnostic reasoning.
The clinician stays responsible for judgment, edits, completion and sign-off. Full interpretive authority at every step.
What took 5–7 hours becomes a review and finalisation workflow. Stronger, more consistent reports - in under 45 minutes.
2x assessment capacity
at zero extra headcount
~£92 → ~£27 per patient
Lower operational cost per report
Consistent, defensible reports at scale
Lower reputational risk and fewer rejections
5–7 hours → under 45 mins
Better reports in significantly less time
Lower burnout risk
Less out-of-hours work, less personal exhaustion
More time for clinical work
Assessment, reasoning, and patient-facing care
Faster access to support
Higher throughput means reduced assessment bottlenecks
Stronger, more personalised reports
More of the patient's voice, more clinical depth
Reduced waiting times
Patients get the help they need sooner
Neurotype solves the problem where it actually exists - deeper and more clinically specific than transcription tools, more focused than broad clinic software, and less disruptive than workflow-replacement platforms.
Built around neurodevelopmental diagnostic logic, evidence structure, conflicting inputs, and nuanced interpretation - not generic note capture or transcription.
Works inside your current workflow, templates, and protocols. No rip-and-replace. No new operating model. You can improve fast because nothing else has to change.
Personalised, clinically coherent, neuroaffirming, and strengths-based. Handles nuance like conflicting evidence and masking - not generic AI output that flattens complexity.
Deep domain expertise, serious data governance, and real-world proof that quality and throughput improve together.
Co-founded and co-designed by a senior clinical psychologist with a neurodiversity and complex mental health specialism.
Secure infrastructure, transparent data handling, and a clinician-in-the-loop workflow that matches the seriousness of regulated clinical documentation.
Neurotype doesn't trade quality for speed. Clinicians consistently report that reports are stronger, more personalised, and more clinically robust - while taking a fraction of the time to produce.
Built with and for experienced diagnostic clinicians across the UK & Ireland.
Healthcare Accelerator
Catalyst Grant
Female Founders Accelerator
Deep clinical experience combined with medical-grade AI engineering.
Jan completed a PhD at St John's College Oxford and a Fulbright scholarship at the University of Pennsylvania before training in Clinical Psychology at UCL. She has worked across NHS and academic settings, specialising in complex mental health, ADHD, and autism. She brings clinical depth shaped by frontline experience and translational research.
Nadezhda has developed medical-grade AI systems across healthcare. With deep experience in machine learning, signal processing, and clinical data pipelines, she focuses on bridging cutting-edge research with safe, reliable real-world clinical implementation.
We're partnering with a select group of pioneering clinics to
co-design the future of neurodiversity care.
Join the waitlist and help shape what's next.