Rizin
Freemium
Users seeking adaptive, non-fixed workout programming
Your blood pressure lives in Omron, your sleep in Oura, your labs in a WhatsApp PDF from your cardiologist, and your glucose in Dexcom — and nothing has ever put them on the same chart until you needed to explain a trend to your doctor. Savva is built for exactly that pile of disconnected health data.
The core workflow is ingestion: connect wearables from a list of 35+ devices, snap paper lab printouts or PDF reports from messaging apps, and Savva merges every reading onto a single biomarker timeline organized into eight groupings. Blood pressure readings land from a home cuff, Apple Watch, clinic visits, and scanned PDFs simultaneously, each ringed by source so you know what generated it. CGM glucose appears alongside logged meals so the two-hour post-meal spike is visible without inference. The AI explanation layer — which covers all of this — is a paid-only feature. Without it, you get the charts; interpretation stays with you.
Bottom line: Pick this if you are managing a GLP-1 titration or a chronic biomarker like HbA1c and want fifteen years of lab PDFs, a wearable feed, and a home cuff on one chart — without a cloud account; skip it if you need API access to pipe your data downstream or want a web-based dashboard your care team can review alongside you.
Free tier with core functionality
AI capabilities localized by country
Localized pricing for lower purchasing power parity markets
View full pricing on savva.ai →
Pricing may have changed since last verified. Check the official site for current plans.
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Freemium
Users seeking adaptive, non-fixed workout programming
Freemium
General medication information seekers
Most people managing a chronic condition or a serious wellness goal are not short on data — they are short on a single place where all of it lands without manual entry, duplicate readings, or a wall of acronyms. Savva pulls from 35+ wearable and home device integrations (Apple Watch, Oura, WHOOP, Garmin, Dexcom, and more), accepts snapped photos of paper lab printouts and PDFs forwarded over messaging apps, and organizes every reading into 22 biomarkers across 8 groupings — with the same biomarker from three different labs collapsing to one continuous line. Everything runs on-device with no account required.
The standout capability is the unified timeline. Blood pressure gets AHA-protocol logging — five-minute rest, two readings averaged, source labeled on the chart — so clinic visits, home cuff readings, and Apple Watch data do not compete; they stack. GLP-1 users log doses in two taps and see dose changes appear as dashed lines directly on the weight curve, making titration impact visible without spreadsheets. CGM users see raw sensor data (no smoothing) paired with logged meals, with personal TIR and GMI targets set against actual readings. The vendor states every formula is visible in the app, so no calculation is black-box.
Savva fits people who are managing multiple data sources and want the reasoning work — correlating a food log to a glucose spike, or a Wegovy dose change to a weight inflection — done by a chart rather than memory. It breaks when you need to share structured data with a clinical team, integrate outputs into another system via API, or access your dashboard from a browser. There is no API, no self-hosted server option, and no web interface listed. The AI explanation layer, which reasons across all ingested data using a choice of 12+ models, is a paid-only feature — without it the tool is a well-organized chart, not an explainer.
On the integration side, the app supports home-screen and lock-screen widgets for one-tap logging of meals, weigh-ins, and doses, reducing the friction that kills most tracking habits. Source labeling on every chart point — distinguishing a clinic reading from a home cuff from a scanned PDF — is built in, so data provenance is never ambiguous.
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