What Is OpenMind's Integration with NEAR AI Cloud? Private AI Processing for Home Robots

OpenMind—an open-source robotics operating system—announced a major integration with NEAR AI Cloud to enable secure, off-device AI model execution for home robots.

This partnership allows advanced AI processing in isolated Trusted Execution Environments (TEEs) using Intel TDX and NVIDIA confidential computing technology, ensuring robot data is encrypted before transmission, processed privately, and returned with verifiable cryptographic proofs. The approach significantly reduces the need for expensive onboard hardware, lowering costs for consumer robots while prioritizing privacy and trust—critical for adoption in sensitive environments like homes and healthcare. Co-founders Jan Liphardt (OpenMind) and Illia Polosukhin (NEAR) emphasized that verifiable trust is essential for mainstream robotics deployment.

How OpenMind + NEAR AI Cloud Works for Private Robot AI

OpenMind’s OS powers robot software stacks, while NEAR AI Cloud provides decentralized, secure compute for heavy AI workloads:

• Data Flow: Sensitive robot data (camera feeds, audio, sensors) encrypted on-device.
• Secure Processing: Runs in hardware-isolated TEEs (Intel TDX + NVIDIA GPUs).
• Verifiable Output: Results returned with cryptographic attestation proofs anyone can independently verify.
• Cost Reduction: Offloads compute from robot hardware, enabling affordable consumer models.
• Privacy Guarantee: No raw data exposure; proofs confirm integrity without revealing contents.

This hybrid edge-cloud model balances performance, privacy, and economics.

• Key Tech: zk-proof attestations, confidential computing.
• Hardware Partners: Intel TDX, NVIDIA confidential GPUs.
• Robot Benefits: Cheaper builds, advanced AI without privacy trade-offs.

Why Privacy and Trust Matter for Home Robotics

CEOs Liphardt and Polosukhin highlighted trust as the biggest barrier to robot adoption in personal spaces:

• Sensitive Settings: Homes, elderly care, healthcare require zero data leakage.
• Current Limitations: On-device AI constrained by hardware costs/power.
• Cloud Risks: Centralized providers raise surveillance concerns.
• OpenMind Solution: Open-source OS + verifiable off-device compute.

The integration aims to make capable, trustworthy robots accessible to everyday households.

• Market Potential: Lower costs could accelerate consumer robotics growth.
• Adoption Drivers: Privacy-first design for healthcare/elderly assistance.
• Broader Trend: Confidential computing in AI + robotics convergence.

Implications for Robotics and Decentralized AI in 2026

This collaboration advances the “private AI” narrative, combining open-source robotics with decentralized cloud compute. As home robots evolve from vacuums to companions, solutions preserving user sovereignty could define winners. NEAR AI Cloud’s role expands its scope beyond blockchain into real-world AI infrastructure.

• Affordability Boost: Reduced hardware needs democratize advanced robots.
• Trust Standard: Cryptographic proofs set benchmark for AI privacy.
• Ecosystem Growth: Attracts developers building on OpenMind/NEAR.

In summary, OpenMind’s December 18, 2025, integration with NEAR AI Cloud enables private, verifiable off-device AI for home robots using TEEs and cryptographic proofs—cutting costs while prioritizing trust in sensitive environments. Led by Jan Liphardt and Illia Polosukhin, this marks a step toward affordable, privacy-first consumer robotics. Follow official channels for demos and updates on this emerging intersection of AI, blockchain, and robotics.