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Fhenix Upgrades Sedona With Confidential FHE to Keep Balances Hidden From AI Agents
Self-custodial trading platform Sedona has partnered with Fhenix to integrate confidential fully homomorphic encryption infrastructure into its system.
Key Takeaways
Cryptographic Security Upgrade
Sedona, a self-custodial trading platform and neo-bank, announced a partnership with Fhenix to integrate Confidential Fully Homomorphic Encryption (FHE) infrastructure into its Arbitrum-based system. The company said the upgrade will ensure key financial data is encrypted by default.
The integration, announced July 15, replaces Sedona’s existing security model based on trusted execution environments with fully homomorphic encryption, according to the companies. Sedona said the change is intended to keep user balances, portfolio positions and artificial intelligence agent spending limits encrypted even during processing, reducing reliance on trusted hardware or operator-based models.
“Sedona is exactly the kind of application Confidential FHE was built for,” said Guy Itzhaki, chief executive officer of Fhenix. “Trading platforms and financial applications need privacy that extends beyond transactions to balances, positions and increasingly the parameters that autonomous agents operate within. By moving from trusted hardware to cryptographic guarantees, Sedona is showing how confidential finance can become a native capability on Arbitrum rather than an optional feature.”
Sedona, founded by Tyler Maxwell, offers spot trading, perpetuals and structured products. The platform is migrating from the Seismic ecosystem to Arbitrum. Sedona said the deployment will occur after that migration is completed, shifting the platform’s privacy model from hardware-based trust assumptions to cryptographic guarantees.
In a statement, the companies said the distinction is important for both users and developers. They noted that many private decentralized finance solutions rely on trusted execution environments, which require users to trust the underlying hardware, or on committee-based approaches that require trust in a set of operators. Fully homomorphic encryption enables computations to be performed on encrypted data without revealing it, the companies said.
Under the integrated model, Sedona users’ balances and positions will remain hidden from AI agents executing inside the system, as well as from other parties.
“We started with TEEs because they were the most practical way to deliver privacy, but our goal has always been to remove trust assumptions wherever possible,” Maxwell said. “Fully homomorphic encryption lets us protect sensitive financial data through mathematics rather than hardware, providing a much stronger foundation for the future of self-custody.”
Sedona said the technical integration is ongoing. Details on timing for the rollout on Arbitrum were not provided beyond the statement that it will follow completion of the migration.