Savva
Summary
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.
Pricing Plans
Subscription- Price
- $9.99/year for AI
- Free Tier
- Core tracking features without AI
Free
Core tracking and charts
- Wearable sync
- Document scanning
- Basic charts
AI
Access to 12+ AI models
- On-device and cloud AI
- Insights across all data
View full pricing on savva.ai →
Pricing may have changed since last verified. Check the official site for current plans.
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Pros
Sign in to edit- Ingests paper lab printouts and PDFs forwarded via messaging apps alongside wearable data, so readings that would otherwise live in a photo album or a WhatsApp thread appear on the same biomarker timeline as your Dexcom feed.
- On-device storage with no account required, which means your HbA1c history and specialist visit notes from 2014 are not sitting on a vendor's cloud server — a meaningful distinction for anyone who has thought carefully about health data exposure.
- Same biomarker from multiple lab sources collapses to one continuous line, so comparing an HbA1c from your GP's lab in 2021 with your endocrinologist's result in 2023 does not require a spreadsheet.
- GLP-1 dose changes appear as dashed lines on the weight curve, so the inflection point where a titration change took effect is visible without cross-referencing two separate logs.
- CGM glucose is displayed as raw sensor data paired with logged meals and a two-hour post-meal reading, so the connection between a specific food and a glucose response is a visual fact rather than a guess.
Cons
Sign in to edit- There is no API and no web interface, so any team or individual who needs to pipe health data into another tool — a care coordination platform, a research export, a custom dashboard — hits a dead end. At that point the data is effectively locked to the device it lives on, and teams with downstream data needs will move to a platform that exposes structured exports.
- AI-powered explanation of labs and biomarker trends is a paid-only feature. Users who stay on the free tier get the aggregated charts but no reasoning layer — which means the interpretation work that justifies pulling all this data together in the first place still falls on the user or their clinician.
- The app is iOS-only based on the page content (Apple Watch integration is foregrounded, no Android devices are listed), so anyone in a household or care situation where Android is the primary device cannot use it at all — a hard stop that sends Android users to a competitor regardless of feature fit.
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About
- Platforms
- iOS
- API Available
- No
- Self-Hosted
- No
- Last Updated
- 2026-07-08T20:30:14.393Z
Best For
Who it's for
- Users managing multiple health data sources
- People tracking GLP-1 or chronic biomarkers
- Individuals preferring on-device privacy options
- Those wanting AI explanations of personal labs
What it does well
- Track blood pressure and weight trends from multiple sources
- Log GLP-1 doses and view impact on weight curves
- Review CGM glucose alongside logged meals
- Digitize and organize paper medical records and PDFs
- Monitor fitness scores and biomarker history in one view
Integrations
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Frequently Asked Questions
- Is Savva free?
- Savva has a permanent free tier alongside paid upgrades (paid plans from $9.99/year for AI). You can keep using a baseline version indefinitely without paying.
- Is Savva open source?
- No — Savva is a closed-source tool. Source code is not publicly available.
- What platforms does Savva support?
- Savva is available on: iOS.
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Curated lists that include this category
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.