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Avinasi Labs Debuts Privacy-Preserving Data Layer for Longevity Science

2025-06-30  |  11:55:14
DeLong data flow architecture chart

A visual overview of DeLong’s secure data architecture, enabling privacy-protected computation and scientific validation on-chain.

Make longevity accessible to everyone, safely.

LOS ANGELES, CA, UNITED STATES, June 30, 2025 /EINPresswire.com/ --

In the past, science was owned by institutions. Health belonged to the privileged few.
Longevity never belonged to us.

For decades, data and experiments stayed locked inside closed systems — while outside, biohackers, researchers, and developers could only wait, consume, and comply.
No access. No feedback. No choice.

But the cracks are showing.
Biotech is accelerating. Bureaucracy can’t keep up.
Research is becoming distributed, computational, and cross-disciplinary — yet funding, data, and trials still need centralized permission.
But some pioneers – the sick, the self-optimizers, the people striving to live long well forever, simply cannot wait.

Because they’ve realized:
“Longevity” isn’t just more years.
It represents the freedom, dignity, and agency individuals seek in shaping their lives.
Healthspan > Lifespan — not just a Darwinian choice, but the reclaiming of health sovereignty, the return of personal power.
For the scientists and developers holding the insights and discoveries to these pioneers’ problems, they can’t afford to wait another two years, not even two months, for results to be published. This knowledge should be known, applied, and built upon — now.


So we built Avinasi Labs —
A system designed to benefit both participants and the progress of longevity research.
Avinasi began with the DeLong platform: a secure infrastructure, where researchers can coordinate experiments, access structured data, and launch their studies; where developers can validate models without waiting for institutional greenlights. DeLong already has 2 million datasets, an open-sourced effort accumulated by scientists in the field in the past 18 years, in collaboration with Vadim Gladyshev’s Lab from Harvard University, and initiated by our co-founder Dr. Albert Ying, who is a PhD from Harvard and now a post-doc at Stanford University and under David Baker’s Lab.

On June 1st, DeLong went live on testnet.
Avinasi welcome you to build with us, a new system that benefits both oneself and longevity research, a starting point for building a new system that changes from sick-care to preventative care. For scientists and developers, this is a system built to empower contribution and innovation: delong.avinasi.ai

Avinasi aims to use the platform to record and reward data contribution, while providing and protecting data privacy.
On top of this foundation, Avinasi is building tools and applications that demonstrate a new longevity lifestyle that those who care to live long want to have.


Avinasi is building the data economy for longevity citizens.
What happens when one’s health data sits idle on a device or is buried in a forgotten PDF?
It becomes passive. Disconnected. Forgotten.
At Avinasi, data isn’t meant to stay passive — it’s meant to move, inform, and create value.
It should move, inform, and return value — to both the individual and the future of health.
With Avinasi’s agent system designed to translate personal health readings into actionable insights — from protocols to nutrition to scientific queries, diagnostics turn into personalized experiments and real-time feedback.

Through DeLong, data flows into secure pipelines — powering open, traceable longevity research. Tasks, incentives, and launchpads turn this into a living system.

In the words of Avinasi Labs co-founder Winnie Qiu:
“With Avinasi, you don’t just track — you participate.
You don’t just contribute — you influence what comes next.
You even get rewarded — for acting on your health, not just watching it.
It’s a data economy built with you.”


To the Longevitists: Avinasi welcomes you.
Become a founding Longevity Citizen.
at avinasi.ai

Yi Ju
Avinasi labs
yi|avinasi.org| |yi|avinasi.org
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