For Health Systems & Commissioners

Chronic conditions need daily care.
Not quarterly appointments.

Allvi extends frontline clinical capacity into the space between appointments — delivering continuous, AI-powered support for patients with hormonal and chronic conditions, and feeding structured longitudinal data back to the clinicians who need it most.

35
Longitudinal data points
generated in 35 days
0
Changes to existing
clinical workflows
48hr
From referral to
patient onboarded
Standard care — data available to clinician
2 data points across 35 days
With Allvi — structured data generated daily
35 structured data points · 4 trigger patterns identified
🔍 AI Insight — Day 10
Stress is the primary driver of this patient's symptom flares. Sleep has minimal independent impact. Management protocol updated accordingly.
18%
Improvement in patient-reported energy levels within 35 days
81%
Reduction in patient-reported anxiety within 35 days
91%
Reduction in joint pain and inflammation within 35 days
35×
More longitudinal data points vs standard quarterly care
The Structural Problem

Frontline clinicians cannot provide what chronic conditions require.

Chronic conditions are not episodic. Their symptoms — fatigue, brain fog, pain, mood disruption — shift day to day, driven by triggers that vary across patients. A fifteen-minute appointment every six months captures a single snapshot of a moving picture.

  • 01 Clinicians make decisions from a snapshot. One appointment every 6–12 months cannot reveal the pattern of triggers driving a patient's symptoms over time.
  • 02 Patients arrive unprepared. They reconstruct months of symptoms from memory, compressing complex overlapping patterns into a 15-minute window.
  • 03 The between-visit burden falls on the system. Unsupported patients make more unnecessary GP and A&E contacts — demand that overstretched frontline workers absorb.
Data available to clinician: 90 days
WITHOUT ALLVI
All symptoms
Appt 1
Appt 2
no data
WITH ALLVI — continuous structured data
Fatigue
Trend: improving →
Anxiety
Correlated with stress events
Joint pain
Rapid improvement from wk 2
Sleep
Minimal change — low trigger weight

Pattern identified: Stress is the primary symptom driver. Sleep has negligible independent impact. This finding cannot emerge from a single appointment — it requires longitudinal data.

How Allvi Works

Three connected mechanisms.
One outcome: better-informed clinical care.

Allvi operates as an extension of frontline clinical capacity — not a replacement. No change to existing workflows. No new systems for clinicians to learn.

01

Continuous Personalised Data Collection

Every daily interaction generates a structured data point across multiple symptom dimensions simultaneously. Over 35 days, that is 35 longitudinal data points — enabling pattern recognition that a single appointment never could.

In one case, Allvi identified that stress was the primary trigger for a patient's symptom flares, while sleep had almost no independent impact — a finding that fundamentally changed her management protocol.
Real-World Evidence Generation
02

Better-Prepared Patients at Every Appointment

Patients arrive with structured longitudinal data — not a vague memory of how they have been feeling. The complexity of overlapping symptoms is already unpacked. Clinicians make faster, more informed decisions in the time they have.

Chronic condition patients typically use 3–5 minutes of a 15-minute appointment reconstructing recent symptom history. Allvi eliminates this entirely.
Clinical Decision Support
03

Reduced System Burden Between Visits

Patients with structured daily support make fewer unnecessary GP contacts and A&E attendances. Allvi absorbs the between-visit demand that currently falls on overstretched frontline workers — without requiring anything from them.

The goal is not to replace clinical interactions but to make them count — by ensuring patients only contact the system when there is something meaningful to address.
Demand Reduction
Digital, AI & Analytics

AI finds the signal.
Clinicians act on it.

Allvi's technology layer operates continuously between appointments — ingesting patient-generated data, identifying patterns, and delivering structured outputs that make every clinical interaction more effective. All clinical decisions remain with the clinician.

Patient Layer · Daily Input

Continuous Data Collection

Structured, daily. Across multiple symptom dimensions simultaneously.

📊
Symptom Tracking
Fatigue, pain, brain fog, mood — scored and timestamped daily
Daily
🍽️
Nutrition & Diet
Food patterns correlated against symptom flares
Daily
😴
Sleep Quality
Duration and quality, weighted against symptom response
Daily
Stress & Activity
Self-reported stress events and physical activity
Daily
💊
Medication Adherence
Timing and consistency — flagged if patterns break
Daily
structured
data in
insights
out
AI & Analytics Layer · Always On

Pattern Recognition & Insight

Continuously analyses longitudinal patient data. Surfaces clinically meaningful signals. Never diagnoses or prescribes.

Trigger Identification
Identifies which specific factors — stress, diet, sleep, activity — drive each individual patient's symptoms over time
Longitudinal Pattern Recognition
Detects trends across 30+ daily data points that no single appointment could reveal
Protocol Personalisation
Adjusts nutrition and lifestyle guidance in real time as the patient's data profile evolves
Deterioration Alerts
Flags when symptom patterns suggest deterioration — before the patient contacts the system
Real-World Evidence Generation
At scale: longitudinal datasets that shift clinical practice for chronic conditions
Clinician Layer · Decision & Action

What Reaches the Clinician

Structured outputs that make every clinical interaction faster and more informed.

📋
Pre-Appointment Summary
Longitudinal symptom trajectory, top trigger patterns, and medication adherence — ready before the appointment begins
🔍
Trigger Profile
Which factors are driving this patient's symptoms — ranked by impact, not assumed by protocol
📈
Response Tracking
How the patient is responding to current management — visible between appointments, not only at review
🚨
Early Warning Flags
Deterioration signals surfaced before the patient seeks urgent care — enabling proactive intervention
🧬
Protocol Recommendations
AI-generated suggestions for the clinical team to review, adjust, and approve — never applied autonomously

All clinical decisions remain with the clinician. Allvi's AI layer surfaces signals and structures data — it does not diagnose, prescribe, or act without clinical oversight. The result: clinicians are better informed at every interaction, and patients receive care that adapts to them between every appointment.

* AI-powered analysis supports clinical decision-making and is reviewed by Allvi's specialist care team. It does not replace clinical judgement, diagnosis, or prescribing authority.

Early Outcomes

Measurable patient outcomes.
Within 35 days.

Initial pilot data from patients with hormonal chronic conditions — thyroid disease, PCOS — managed through Allvi's continuous care model. Clinical study protocol in development.

18%
Improvement in energy levels
Patient-reported energy improvement — measured daily, not estimated at a review appointment. Enables objective tracking of intervention response over time.
Within 35 days · PCOS & thyroid cohort
81%
Reduction in anxiety
Anxiety is one of the most clinically significant and under-managed symptoms of hormonal conditions. Daily structured tracking enables real-time intervention before it escalates.
Within 35 days · PCOS & thyroid cohort
91%
Reduction in joint pain
Rapid symptom improvement from personalised nutrition and lifestyle protocols — adjusted in real time as the patient's data profile evolves. Not protocol-driven. Patient-specific.
Within 35 days · PCOS & thyroid cohort
Case Study — Stress Trigger Identification

A finding that changed a patient's management protocol.

Over 35 days of structured daily data collection, Allvi's AI identified that stress was the overwhelmingly primary driver of a patient's symptom flares — while sleep, the assumed primary factor, had almost no independent impact. This finding could not have emerged from a single appointment. It required longitudinal data.

What the data showed
Stress events → Symptom flare within 48 hours in 89% of instances

Poor sleep alone → Negligible symptom impact when stress was absent

Protocol change: Shifted focus from sleep hygiene to stress management — resulting in a 91% reduction in joint pain and 81% reduction in anxiety within the same 35-day window.

Patient-reported outcome measures from initial pilot cohort. Clinical study protocol in development. Individual results may vary.

Who We Work With

Built for health systems,
commissioners, and integrated care.

Allvi is designed for partnerships with NHS organisations, ICBs, PCNs, and private health providers managing chronic condition populations at scale.

🏥

NHS Integrated Care Boards

Allvi supports ICBs in reducing the between-visit demand burden on overstretched primary care — while improving outcomes for chronic condition populations.

  • Reduced unnecessary GP contacts
  • Lower A&E attendance from unsupported patients
  • Population-level longitudinal data for planning
  • No clinical workflow changes required
🩺

Primary Care Networks

Allvi extends the capacity of GP practices and practice nurses — providing the ongoing support that chronic condition patients need, without increasing clinical headcount.

  • Patients arrive with structured data at every appointment
  • Faster, more informed clinical decisions
  • Medication adherence monitoring between reviews
  • Early flagging before patients escalate to urgent care
🔬

Digital Health Accelerators & Programmes

Allvi is seeking partnership with digital health innovation programmes — including NHSX, Grow Digital Health, and regional innovation hubs — to pilot and evaluate the model at scale.

  • Pilot design co-developed with health system partners
  • Shared outcomes reporting framework
  • Real-world evidence generation for commissioning
  • Regulatory and integration pathway support
Partnership Models

How we work together.

Allvi is designed to be deployed alongside existing care pathways — as a structured pilot, a commissioned service, or an integrated referral pathway.

Commissioned Service

Per-Patient Deployment

For health organisations ready to commission Allvi as a structured chronic condition self-management and early intervention service.

  • Per-patient-per-month model — costed on request
  • Deployed across a defined patient population or pathway
  • No clinical staff redeployment required
  • Structured outcomes reporting for commissioning review
  • Integrates with existing referral pathways
Ready to explore a pilot?

The data clinicians need is being generated every day.
Allvi makes it available.

We are actively seeking NHS and health system pilot partnerships. If you are responsible for chronic condition pathways, digital health innovation, or integrated care commissioning, we would like to speak with you.

Or reach us directly at support@allvihealth.com · allvihealth.com