In a significant push for user sovereignty in artificial intelligence, the NEAR AI team has launched two products designed to make privacy and verifiability core features of AI interaction. NEAR AI Cloud and NEAR Private Chat leverage confidential computing hardware and cryptographic proofs to allow users and developers to utilize AI with sensitive data while maintaining full control and compliance.
NEAR AI has launched two new products focused on verifiable privacy: NEAR AI Cloud and NEAR Private Chat.
The core technology uses confidential computing (Intel TDX, NVIDIA) in Trusted Execution Environments (TEEs) to isolate and protect data.
Every AI request includes a cryptographic proof that can be independently verified, proving data was processed privately.
NEAR Private Chat offers an encrypted interface to open-source AI models, ensuring conversations are not logged or used for training.
The platform is already in production with launch partners including privacy browser Brave, Phala Network, and robotics OS OpenMind.
NEAR AI Cloud is compatible with the OpenAI API for easy developer migration and is built for high-throughput, low-latency performance.
This launch represents a concrete step toward a vision where individuals and businesses retain ownership and control over their data in AI interactions. The fundamental argument is that true AI utility, especially with sensitive context, requires guarantees beyond policy, necessitating hardware-level isolation and mathematical proof. Illia Polosukhin, founder and CEO of NEAR AI, stated, “Everyone should own their AI. Today NEAR AI is taking a major step towards the vision of user-owned AI with the launch of private, verifiable AI products. Privacy and verifiability are required to maximize available AI context for users and businesses, with confidentiality and compliance thanks to hardware- and cryptography-based guarantees.”
NEAR AI Cloud moves confidential computing from a theoretical concept to a production-ready service for developers and enterprises. By running AI models within secure TEEs, it ensures that not even NEAR or the hardware providers can access user data during processing. The groundbreaking feature is the attached cryptographic proof for each request, which provides an auditable, transparent record of how and where data was handled. Marvin Tong, CEO of Phala Network, remarked, “We’ve waited years for a system that can prove privacy at scale. NEAR is the first to deliver.”
To demonstrate the practical application of this technology, NEAR also released Private Chat. This tool acts as a secure gateway to leading open-source models, allowing users to ask sensitive questions—related to finance, health, or proprietary business information—without the fear of data leakage or model training. Polosukhin emphasized this commitment: “Everyone deserves access to powerful AI without giving up their privacy. We made Private Chat to prove that’s possible. Literally.”
The platform is not merely conceptual, with several notable partners already integrated. Brave Browser is utilizing it to enhance the verifiable privacy promises of its AI assistant, Leo. Brian Bondy, CTO and co-founder of Brave, noted, “We’re excited to work with NEAR to offer verifiable privacy and transparency.” Similarly, OpenMind’s robotics operating system employs it for secure data processing in sensitive physical environments like homes and hospitals.
For adoption, NEAR AI Cloud prioritizes developer familiarity by offering OpenAI API compatibility, allowing for straightforward migration of existing applications. SDKs simplify encryption and key management. The launch is positioned as the first phase of a broader roadmap aiming to build a full stack for user-owned AI, including encrypted memory, AI agents, and decentralized coordination secured by the NEAR blockchain.
This launch directly challenges the prevailing data-handling models of major AI providers by offering a technically enforced alternative. It provides a compelling infrastructure for industries with strict compliance needs and for any user prioritizing true data sovereignty in their AI interactions, marking a pivotal moment for privacy-preserving technology.
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