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Side-by-side

See vasus.ai in action — inside a connected-care app

Two views of the same migraine companion app. On the left, the dashboard as it ships today — a polished tracker with a generic weather widget. On the right, the same dashboard with a vasus.ai Environmental Health Insight added: cited, condition-specific, and grounded in peer-reviewed evidence.

Without vasus.ai

A connected-care migraine app as it ships today.

A widget weather data is shown — but never explained
9:41
Demo · fictitious app
Hello Lisa
Here’s your 30-day summary
80%
Schedule success
2
Acute meds
Your care plan
Your medications for today
Log your symptoms today
HIT-6 this month
Today in London, Greater London
14°
16° / 9°
Pressure1009 mb
Humidity78%
Air qualityGood
via a third-party weather feed
Home
Medication
Symptoms
  • ✓Tracks medication, symptoms and adherence well
  • ✓Includes a basic third-party weather widget
  • ✓Familiar, polished patient experience
  • ×Weather data is shown — but never linked to migraine
  • ×No evidence or citations behind the numbers
  • ×No risk level, no synthesis, no trigger context

With vasus.ai

The same app, with a vasus.ai insight layer added.

An insight a cited Environmental Health Insight on every check-in
9:41
Demo · fictitious app
Hello Lisa
Here’s your 30-day summary
80%
Schedule success
2
Acute meds
Your care plan
Your medications for today
Log your symptoms today
HIT-6 this month
Today in London, Greater London
14°
16° / 9°
Pressure1009 mb
Humidity78%
Air qualityGood
via a third-party weather feed
Environmental Health Insight
London, UK
Migraine & weather · next 24 hours
Moderate risk
A rapid frontal passage is driving a 6.2 mb barometric pressure drop over the next 24 hours, with pressure volatility elevated across the full 72-hour window — a pattern repeatedly associated with migraine onset in the weather-sensitivity literature. Humidity is climbing after recent rainfall. Two of Lisa’s logged episodes this season fell on comparable frontal-passage days, so this is a useful signal to surface ahead of today rather than after it.
1 Prince et al. (2017) — Barometric pressure and migraine: meta-analysis of 7 studies. Headache, 57(8).
2 Hoffmann et al. (2015) — Weather sensitivity in migraineurs. Journal of Neurology, 262(4).
vasus.ai EHSPI v1.6 5 signals 2 citations
Home
Medication
Symptoms
  • ✓ Everything the app already does, plus:
  • ✓Existing user profile enriched with environmental insight
  • ✓Cited environmental factors, every check-in
  • ✓Specific trigger candidates, not guesses
  • ✓Peer-reviewed sources behind every claim
  • ✓Better personalised user experience
  • ✓Bring your own data — your own environmental metrics or user profile information can be used with the vasus.ai intelligence layer
  • ✓Build a hyper-localised, holistic view of the factors affecting your users’ condition
  • ✓Better contextualise triggers, pre-clinical audit trails and your AI agent responses
  • ×Requires a one-time API integration
Use case · Digital health app

Condition management apps

Add an evidence-based environmental risk layer to further personalise user daily check-ins — without building the science.

1 API call
Risk level, signals, synthesis paragraph, inline citations — tailored to the user's condition.
The problem

Users of condition management apps — migraine trackers, asthma diaries, sleep apps — already log their symptoms. But they have no in-depth way to connect what happened environmentally to what they experienced. The app captures the outcome — not the trigger.

The solution

vasus.ai adds environmental context to every check-in. Each morning, the app calls POST /v1/insight with the user's home location and condition specifics. The non-clinical response includes a risk level, the three most relevant signals, a synthesis paragraph grounded in peer-reviewed evidence, and cited recommendations — in one structured JSON response that merges with existing user attributes.

The outcome

Users see "Moderate migraine risk today — barometric pressure dropped 6.2 mb overnight" with two citations, not just a weather widget. The app becomes clinically meaningful, building trust and traction with users — without the product team building any environmental science.

Integration steps

Four steps to ship

1
On app open or daily check-in
POST /v1/insight with condition + stored home location + window=24
2
Display risk chip in dashboard
risk_level from response. Green/amber/red badge. No custom logic needed.
3
Surface synthesis paragraph
summary field. Plain English. Cite the top_matches citations inline.
4
Optional: enable push alerts
POST /api/alert/subscribe once. Hourly monitor fires Web Push when threshold met.
Relevant sensitivities
migraine respiratory cardiovascular sleep allergies
Relevant for: migraine tracker apps, asthma management apps, COPD management, sleep quality apps, pollen allergy apps.
Try it live ↗ Discuss this integration →
Want to go deeper?
Read the methodology
Weight vectors, citations, and the EHSPI scoring methodology — all transparent.
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See the API reference
All endpoint params, response fields, auth patterns, and integration examples.
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Talk to the founder
For founding-partner conversations, pricing, or technical questions.
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