AxonDAO partnered with SKALE to launch a gas-free platform where users control encrypted health data and earn AXGT for research access.

AxonDAO (AXGT) is building a decentralized health data operating system where individuals store medical records in encrypted vaults and rent consented access to researchers for AXGT rewards. 

To run that vision at scale, the project has teamed with SKALE Network (SKL).

The integration means every consent toggle, data query, and reward payout settles in seconds without users paying transaction fees. That wipes out two of Web3 healthcare’s biggest frictions: gas anxiety and slow finality.

AxonDAO already claims forty-five thousand token holders and a slate of research partners interested in tapping real-world data sets. With SKALE’s elastic sidechain model, the platform can spin up dedicated compute clusters that isolate sensitive workloads from public chatter while keeping them verifiable on-chain. 

Researchers launch studies directly on the network, run algorithms inside privacy-first sandboxes, and pay contributors from a shared liquidity pool. Participants keep full control of their vault keys and can revoke access any time, solving a trust gap that plagues traditional data brokers.

The choice of SKALE leaned on three points: human support, sub-second finality, and zero gas. For a system that logs consent events and handles large data payloads, fee-free execution is more than a perk; it is the only way the model makes economic sense. 

The chain’s bridge to Ethereum also lets AxonDAO tap deeper liquidity without exposing users to mainnet fees.

Strategically, the launch blends three hot narratives: DePIN for decentralized infrastructure, DeSci for open science, and gas-free UX for mass adoption. If the stack proves reliable, AxonDAO might become the default rail for ethical AI models needing regulated data.

It remains to be seen whether SKALE can scale with the growth and number of users that AxonDAO is targeting. 

Failure would reinforce doubts that on-chain privacy tech can ever match HIPAA-grade standards. Early pilots will reveal whether medical institutions feel safe enough to plug in sensitive datasets.

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