Assistiv Early Screening for Independent Living in the Community
Assistiv tools are a community-based frailty screening and intelligence system built for the NHS. These tools help to identify older adults at risk before a crisis, give them something of genuine value from the process, and equip clinical teams with the intelligence they need to respond effectively.
What every person hears before a single question is asked
“You might have arrived here thinking this is about what happens when things go wrong. It’s actually about making sure things go the way you want.”
Nothing is assessed without agreement. Nothing is shared without permission. The conversation belongs to the person, and so does everything it produces.
There is a population of older adults in the UK who are too frail to be fully safe at home but not yet eligible for formal NHS or social care support. They fall between the thresholds. They are one fall, one infection, or one carer breakdown away from an acute hospital admission, often avoidable.
The NHS frailty system is reactive. People appear in it when they arrive at A&E or when crisis has already happened. Proactive community identification of frailty risk, before the system has to respond, barely exists at scale anywhere in the country.
For every older adult who loses their independence to an avoidable crisis, there is a family under strain, a carer invisible to health services, and a preventive opportunity that passed without anyone seeing it. Assistiv is designed to see it.
Assistiv asks older adults about their everyday life in a conversational, voice-first interface powered by Claude Sonnet. They speak freely, in their own words, at their own pace. The AI listens: not just to what is said, but to how it is said. It detects hesitation, minimisation, and the specific fears that prevent older adults from disclosing vulnerability: the fear of being a burden, and the fear of what honest disclosure might lead to.
From a single conversation, Assistiv generates a personalised Wellness Guide for the person, a structured clinical referral for the frailty team, and, with consent, a population intelligence signal for NHS commissioners. Three distinct outputs. One dignified, human conversation. Nothing shared without explicit permission.
A voice-first community frailty screen that interprets free spoken responses using Claude. Twelve conversational questions across six life domains. Adaptive language for four completing-party types. Safety architecture built throughout.
Open tool → LiveAn independent observational questionnaire for a nominated carer, linked by consent only. The carer's scores never reach the person; the person's scores never reach the carer. The comparison happens at the clinical layer, where it generates the most value.
Open tool → SimulationA structured referral document for the frailty team, centred on a Frailty Profile Radar, a six-spoke diagram that communicates the person's risk profile at a glance. Domain detail, minimisation notes, referral priorities, and a CGA preparation brief.
This tool shows a simulation of how clinical referral outputs will be presented. It is not yet connected to live screening data.
View simulation → SimulationWhen both a person's screen and a carer's report are available, two profiles overlay on the radar. Agreement confirms clinical confidence. Divergence is a clinical signal, almost always indicating that the person is understating genuine difficulty.
This tool shows a simulation of how dual person and carer outputs will be presented side by side. It is not yet connected to live screening data.
View simulation → SimulationA population-level frailty intelligence interface for NHS commissioning teams. Geographic ward-level risk mapping, domain analysis, referral demand forecasting, and an AI-synthesised commissioning brief from the full anonymised dataset.
This tool shows a simulation of how population intelligence outputs will be presented to commissioning teams. It is not yet connected to live screening data.
View simulation → SimulationThe synthesis layer. Person self-report, carer observation, and CGA clinical findings overlaid on a single radar, three independent perspectives on the same person. In this simulation, where all three confirm significant need, the Triple Tap is the highest confidence signal in the system.
View simulation →Unpaid carers are the invisible infrastructure of health and social care. They coordinate between departments that do not speak to each other, catch medication errors the system should catch, and absorb a level of clinical and administrative complexity that no single person should carry alone. We are building tools to change that.
A single place that holds the complete clinical picture — appointments, letters, contacts, documents, symptoms across departments. Because no one should have to carry nine medical teams in their head.
Proactive surfacing of what exists — grants, assessments, groups, next steps — before the carer reaches breaking point. A direction, not a signposting loop.
Flagging potential contradictions in clinical advice and surfacing symptoms that slip between departments — routed immediately to the right professional. These tools surface and prompt. They never adjudicate.
Structured preparation for clinical appointments, question builders, and plain-language summaries of complex medical material — building the carer's confidence to communicate, not replacing their voice.
"I felt absolutely alone through all of this, left entirely without any acknowledgment, guidance, or support."
Primary source — carer of a stroke and cardiac surgery survivor, sole coordinator across nine NHS departments
Assistiv gives before it asks. Every person receives a personalised Wellness Guide, regardless of what they choose to share with clinical services. The guide belongs to them.
You are the author of your own life. Nothing happens without the person's permission. Every consent layer is granular, revocable, and explained in plain language.
Everyone wants the same thing. The older person, the carer, and the clinical team all want the same outcome: safe, well, and at home, on the person's own terms. Assistiv closes the information gap between them.
The AI is always under human control. Assistiv tools uses Claude Sonnet to interpret spoken responses and generate outputs, but the AI operates within a tightly defined set of instructions written by the development team. It does not act freely: it follows a clear clinical framework, asks only the questions it is given, and interprets responses only within the domains it is designed to address. This is a working prototype, and the instruction set will be refined in direct partnership with geriatricians, frailty nurses, and clinical researchers. The system learns through that collaboration, not independently.
Privacy is built in, not bolted on. Assistiv is designed from the outset to be GDPR-compliant by default. No personal data is stored, transmitted, or shared unless the person explicitly chooses to share it. The three-layer consent model gives each individual granular control: a person can receive their Wellness Guide and share nothing further. Data used for population intelligence is anonymised before it leaves the device. There is no profiling, no third-party data sharing, and no commercial use of personal information. Privacy is not a feature of Assistiv. It is the foundation.
British Geriatrics Society self-screening frailty identification instrument, embedded invisibly across the twelve screening questions and scored in real time.
Fatigue, Resistance, Ambulation, Illness, and Loss of weight domains mapped across Physical Function, Nutrition, and Medical Burden question categories.
British Geriatrics Society framework informing question categories, clinical domain structure, and referral routing throughout the tool suite.
Finnish Geriatric Intervention Study: multidomain intervention evidence base underpinning the personalised Wellness Guide structure and recommendations.
NHS RightCare Frailty Pathway informing clinical triage logic, referral routing, and priority weighting within the Clinical Referral tool.
Peer-reviewed evidence covering oral frailty indicators and sleep disruption as supplementary life domains within the screening architecture.
A 2025 peer-reviewed study in Geriatric Nursing (Zhang et al., DOI: 10.1016/j.gerinurse.2024.10.025) tested nine machine learning models for predicting frailty in older adults. The best-performing model identified pain level, depression, and functional ability as the three strongest predictors, outperforming objective physical measures. Notably conducted in a chronic pain population, the finding that subjective, self-reported experience carries greater predictive weight than clinical history directly supports Assistiv's conversational, voice-first approach to eliciting what standardised forms cannot.
Assistiv is a working prototype, developed in response to a real clinical need and grounded in validated evidence frameworks. The clinical domain structure and question architecture have been informed by informal conversations with geriatric specialists and frailty practitioners. The next stage is formal co-development: working directly with those at the cutting edge of delivering support and interventions to this population, to test, challenge, and strengthen every aspect of the system.
Assistiv is for you if you want to stay living well at home and would like to understand what support might help, on your own terms, at your own pace.
Assistiv is for frailty nurses, geriatricians, Neighbourhood Health Service coordinators, and GP practices who need to identify at-risk patients in the community before crisis, not after.
Assistiv is for ICB commissioners and NHS system leaders who need population-level frailty intelligence to inform commissioning decisions, identify service gaps, and target preventive investment.
Assistiv is not a clinical assessment and it is not a form. It is a conversation about your everyday life. It will ask you about things like how you are sleeping, whether you feel confident getting around, and what matters most to you about staying at home. At the end, it gives you a personalised Wellness Guide that belongs to you. Nothing is passed on to anyone unless you choose to share it.
Maybe things feel a little harder than they used to. Maybe you are managing fine but would like to understand what support is available before you need it. Assistiv asks you about your life in your own words, at your own pace, and gives you something genuinely useful in return. No waiting room. No referral needed. Just a conversation.
Try the conversation →Adult children often notice things before anyone else does. A parent who seems a little more tired, a little less steady, a little more reluctant to talk about how they are getting on. If you have noticed something and are not sure what to do next, Assistiv can help you understand the picture more clearly, and give your family member something valuable in the process.
Learn how it works →Social prescribing link workers, community pharmacists, voluntary sector workers, and faith community leaders are often the first to sense that someone is struggling. Assistiv gives you something to offer in that moment: a dignified, voice-first conversation that produces a Wellness Guide the person can keep, and, if they choose, opens a pathway to clinical support.
Talk to us about your work →"The guide is yours. We give it to you regardless of what you choose to do next. Nothing leaves this conversation without your permission."
Assistiv operates across three integrated platforms. Each addresses a distinct stage of the journey from invisibility to appropriate support — finding people, understanding their needs, and delivering the right response.
01
Identify
assistiv.cloudPopulation-level frailty intelligence. Finds older adults in the Missing Middle before they reach crisis — using open NHS data, geographic signals, and longitudinal risk modelling.
Intelligence layerRefer
02
Screen
assistiv.toolsCommunity screening for identified populations. Determines the level and urgency of need through structured, validated assessment — sorting those who need acute pathways from those suited to early intervention.
You are hereRoute
03
Intervene
assistiv.servicesEarly intervention for those below the acute threshold. Passive home monitoring, warm conversation, and care coordination — delivered on the person's terms before independence is lost.
Early interventionAcute pathway
Health and Social Care
People approaching or exceeding the acute threshold are referred directly into NHS or local authority care pathways — with the longitudinal data needed for rapid, accurate assessment.
Early intervention pathway
Assistiv Services
People below the acute threshold — managing, but at risk — are supported by Assistiv's platform. Proactive, non-intrusive, and designed to extend independence and defer the need for formal care.
Assistiv tools is developed by Assistiv Systems. If you are a clinician, researcher, or specialist working in this field and would like to explore the prototype or offer feedback, we would welcome the conversation.
simon@assistiv.co