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License: License: unverified
Local-run terms: Desktop application installed and run entirely on the user’s machine with local data storage.

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OpenLongevity

FreeOpen SourceSelf-Hosted

Pricing

Model
Free

Summary

Longevity research tools built for the cloud ask you to upload your supplement stack, your labs, and your protocol to a platform you don't control — then lock the context behind a subscription. Open Longevity is a self-hosted desktop application that keeps your evidence library, AI keys, and personal plans entirely on your own machine.

The tool organizes longevity literature into a three-panel layout: a knowledge map on the left, traceable evidence in the center, and personal plans on the right — no developer tooling required to run it. Drop a paper link or abstract into the AI capture layer and it extracts the research target, outcomes, limitations, and source before asking whether to save. Interventions are tiered by evidence maturity rather than fake precision scores, from foundation habits down to frontier compounds. Where it breaks: the AI layer requires you to supply your own API key for OpenAI, Anthropic, or a compatible endpoint — no key, no AI features. Teams expecting an opinionated, pre-loaded evidence database will find the starting content is scaffolded around publicly available protocols, not a curated clinical corpus.

Bottom line: Pick this if you want a private, local research workbench for building and iterating a personal longevity protocol; skip it if you need a multi-user platform, shared team knowledge bases, or a pre-validated clinical evidence database you don't have to populate yourself.

Community Performance Report Card

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Best For: Individuals seeking structured, local longevity research tools, Users who want AI assistance without cloud data uploads, Researchers tracking evolving supplement and protocol evidence
  • All data — notes, plans, API keys, and the knowledge library — stays in local storage on your machine, so there is no platform dependency or data exposure risk for sensitive health information.
  • Bring-your-own-model design supports OpenAI, Anthropic, and any compatible custom API endpoint, so you are not locked to a single provider and can swap the underlying model when pricing or capability shifts.
  • The AI capture step extracts research object, outcomes, limitations, and source from a paper or abstract and holds for your review before saving, which means your library stays curated rather than filling with unverified noise.
  • Evidence maturity tiers (Foundation through Frontier) make the confidence level of each intervention explicit, so you are not acting on a T5 frontier compound with the same confidence as a T1 habit.
  • Open-source codebase with self-hosted installation means you can inspect what the tool does with your data and modify it — something no SaaS longevity platform in this category offers.
  • The AI features require you to supply, configure, and pay for your own LLM API credentials; someone who does not have an OpenAI or Anthropic account and is not comfortable managing API keys gets a research organizer with no AI capability at all.
  • There is no multi-user or shared workspace layer, so a research team or household trying to maintain a shared evidence library and protocol cannot collaborate inside the tool — at that point teams move to a general-purpose knowledge base like Notion or Obsidian with manual evidence tracking.
  • The starting evidence library reflects publicly available protocols rather than a curated clinical corpus, which means the burden of populating a credible, source-checked database falls entirely on the user — researchers expecting pre-loaded, reviewed intervention data will find the tool is an organizer, not an evidence source.
  • macOS installation requires a manual terminal command to clear extended attributes before the app will run; users unfamiliar with the terminal face a barrier at first launch that has no in-app resolution path.

About

Platforms
Windows, macOS, Linux
API Available
No
Self-Hosted
Yes
Last Updated
2026-08-14T04:10:50.826Z

Best For

Who it's for

  • Individuals seeking structured, local longevity research tools
  • Users who want AI assistance without cloud data uploads
  • Researchers tracking evolving supplement and protocol evidence

What it does well

  • Organizing longevity literature with traceable references
  • Capturing and summarizing new papers or ideas with AI
  • Maintaining and iterating personal supplement and lifestyle plans
  • Comparing evidence maturity across interventions

Integrations

OpenAIAnthropiccustom API endpoints
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Frequently Asked Questions

Is OpenLongevity free?
Yes — OpenLongevity is fully free to use. There is no paid tier.
Is OpenLongevity open source?
Yes. OpenLongevity is open source.
Can I self-host OpenLongevity?
Yes. OpenLongevity supports self-hosting on your own infrastructure.
What platforms does OpenLongevity support?
OpenLongevity is available on: Windows, macOS, Linux.

Cloud longevity platforms force users to upload sensitive health data and lock plans behind subscriptions.

Open Longevity runs as a self-hosted desktop application on Windows, macOS, and Linux. It keeps notes, plans, API keys, and the evidence library in local storage with no platform uploads.

Three-panel layout and AI capture

The interface shows a knowledge map on the left, traceable evidence in the center, and personal plans on the right. Users drop a paper link or abstract into the AI capture layer; the tool extracts research target, outcomes, limitations, and source, then asks whether to save. Interventions are grouped by evidence maturity from foundation habits to frontier compounds.

Model and data control

The AI layer works with a user-supplied key for OpenAI, Anthropic, or any compatible endpoint. No multi-user workspace is included.

Who it is for / who should skip it

Best for individuals who want structured local longevity research tools and AI assistance without cloud data exposure. Researchers tracking supplement evidence also fit. Skip it if you need shared team workspaces or prefer not to manage your own LLM API keys.