OpenVitals

Built to make your health data extraordinarily clear, OpenVitals is the best way to understand your records.

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OpenVitals
LDL Cholesterol
98mg/dL
↓ 14
HbA1c
5.9%
↑ 0.3
Ferritin
14ng/mL
↓ 8
Vitamin D
22ng/mL
↓ 6
Metric
Value
Reference
Status
Trend
LDL Cholesterol
98mg/dL
0–100
Normal
HDL Cholesterol
58mg/dL
> 40
Normal
Triglycerides
162mg/dL
< 150
Borderline
HbA1c
5.9%
< 5.7
Borderline
Ferritin
14ng/mL
20–300
Low

Parses lab reports from the most common providers

Upload a PDF,
get structured data

Accelerate understanding by handing off messy lab reports to OpenVitals. AI classifies, extracts, and normalizes — you focus on the results.

Learn about ingestion →
quest_labs_mar2026.pdf
Lab report
0.96Completed18
physical_notes.pdf
Encounter note
0.84Parsing...
dental_xray_summary.pdf
Dental record
0.62Needs review7
Provenance chain screenshot

Every value traces back to its source

Click any observation and see the full chain: source PDF, parser version, LOINC code, confidence score. No black boxes.

Learn about provenance →
How have my lipid panel results changed over the last year?
OpenVitals AI
Your lipid panel shows meaningful improvement. LDL dropped from 142 to 98 mg/dL — now within optimal range. However, triglycerides trended up to 162 mg/dL.
◎ 6 observations◷ Mar 2025–2026⟐ Quest + LabCorp
Ask about your health data...

AI that only speaks from your records

Ask questions about your health data and get answers grounded in your actual observations. Every response cites the data it used.

Learn about AI chat →

Works across all your sources

AI context bundles pull observations from Quest, LabCorp, manual entries, and wearable exports. One unified view across all your health data.

Learn about context bundling →

Share exactly what your doctor needs

Create scoped shares by category, time range, and access level. Your cardiologist sees lipids and vitals. Your nutritionist sees diet-related labs. Nobody sees what they shouldn't.

Explore data sharing →
Sharing UI screenshot
Medication tracking screenshot

Medication tracking with full context

Active medications, supplements, dosage, frequency, and daily adherence — all linked to your health timeline and lab results.

Learn about medications →

The new way to own your health data.

I finally understand my lab results without having to Google every acronym. The provenance chain is brilliant — I can show my doctor exactly what changed.

SM
Sarah M.
Patient, annual lab tracking

The scoped sharing is exactly what I needed. My endocrinologist only sees thyroid panels and nothing else. Privacy should always work this way.

JR
James R.
Managing hypothyroidism

Open source health data infrastructure is long overdue. The plugin SDK means the community can add parsers for any lab format.

DPK
Dr. Priya K.
Health tech researcher

Being able to trace every value back to the source PDF with one click is incredible. No more wondering where a number came from.

MC
Michael C.
Tracking lipid trends

The AI chat is grounded in my actual records — not generic medical knowledge. It cited specific observations from my Quest results.

EV
Elena V.
Managing chronic conditions

I've used five different health apps. This is the first one where I feel like I actually own my data. The export and provenance features are unmatched.

DL
David L.
Quantified self enthusiast

Stay on the frontier

Ingestion

Use the right parser for every lab

Quest, LabCorp, hospital systems, and CSVs. The pipeline classifies, extracts, normalizes, and maps to standard codes.

Medications

Complete medication understanding

Track medications, supplements, dosage, adherence, and interactions — all linked to your health timeline.

Plugins

Developer-first plugin ecosystem

Build custom parsers, views, and analyzers with the SDK. Register new metrics, add data sources, publish to npm.

Changelog

Mar 15, 2026
AI chat with provenance
Mar 10, 2026
Medication tracking
Mar 4, 2026
Scoped data sharing
Mar 1, 2026
Lab PDF ingestion pipeline
See what's new in OpenVitals →

OpenVitals is an open-source project focused on giving people control over their health data.

Contribute on GitHub →
Team / community image