NeuroWell Hub: Giving Clinicians Their Time Back by Automating Mental Health Risk Assessment Reports

Brief

NeuroWell Hub’s clinicians were spending hours writing up mental health risk assessment reports by hand, translating PHQ-9 and GAD-7 results into a structured, personalised report for each client. We built an AI system that ingests those uploaded documents, understands what the tools are actually measuring, and generates a report in a format shaped directly with NeuroWell Hub’s own mental health experts. Hosted on Microsoft Azure with all data kept in Australia and never used to train AI models, giving clinicians more time back for the clients in front of them.

Problem

Every client who comes through a mental health service completes standard assessment tools like the PHQ-9 and GAD-7, and someone still has to turn those raw results into a proper risk assessment report. That work fell entirely to clinicians, reading through each form by hand and writing up a personalised report for every single client. It’s careful, necessary work, and it’s also time that could be spent directly with the people who need it.

NeuroWell Hub needed a way to take that manual write-up off their clinicians’ plates without losing the clinical judgement that makes these reports trustworthy. That meant building something a mental health service could actually stand behind: an AI that understood these specific assessment tools, produced reports in a format their own experts had signed off on, and kept every piece of client data secure and onshore.

Solution

A clinician uploads a client’s completed PHQ-9, GAD-7 or similar assessment documents through a simple web interface. The AI reads and understands the content, then generates a personalised risk assessment report in a format built and refined directly with NeuroWell Hub’s mental health experts, ready to download.

• Shaped by real clinical expertise, not assumptions: the report format and the AI’s understanding of what each tool measures were built through direct workshops with NeuroWell Hub’s own mental health experts, not guessed at from the outside.
• Tested against real files with the people who’d use it: the system was tested across many real assessment documents alongside NeuroWell Hub’s team until they were confident in its accuracy.
• Built for clinical-grade data handling: hosted on Microsoft Azure, with all data kept in Australia and never used to train AI models.
• A clear path beyond the MVP: areas where a general-purpose AI model fell short were identified and mapped into a roadmap for purpose-built machine learning models down the track.

Result

NeuroWell Hub went from a concept to a fully built platform their team could actually use. Reports that used to take a clinician’s own time to write by hand are now generated automatically, freeing up hours that go straight back into time with clients, improving the service NeuroWell Hub can offer and supporting revenue growth in turn. The system was tested extensively with NeuroWell Hub’s own mental health experts before being signed off, so the reports reflect real clinical judgement, not just an AI’s best guess.

Under the Hood