Privatemode AI Description
Privatemode offers an AI service similar to ChatGPT, distinguished by its commitment to user data privacy.
By utilizing confidential computing techniques, Privatemode ensures that your data is encrypted right from your device, maintaining its protection throughout the AI processing stages. This guarantees that your sensitive information is safeguarded at every step.
Key features include:
Complete encryption: Thanks to confidential computing, your data is continuously encrypted, whether it is being transferred, stored, or processed in memory.
Comprehensive attestation: The Privatemode application and proxy confirm the integrity of the service using cryptographic certificates issued by hardware, ensuring trustworthiness.
Robust zero-trust architecture: The design of the Privatemode service actively prevents any unauthorized access to your data, including from Edgeless Systems.
EU-based hosting: The Privatemode infrastructure is located in premier data centers within the European Union, with plans for additional locations in the near future.
This commitment to privacy and security sets Privatemode apart in the landscape of AI services.
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Phala
Phala provides a confidential compute cloud that secures AI workloads using TEEs and hardware-level encryption to protect both models and data. The platform makes it possible to run sensitive AI tasks without exposing information to operators, operating systems, or external threats. With a library of ready-to-deploy confidential AI models—including options from OpenAI, Google, Meta, DeepSeek, and Qwen—teams can achieve private, high-performance inference instantly. Phala’s GPU TEE technology delivers nearly native compute speeds across H100, H200, and B200 chips while guaranteeing full isolation and verifiability. Developers can deploy workflows through Phala Cloud using simple Docker or Kubernetes setups, aided by automatic environment encryption and real-time attestation. Phala meets stringent enterprise requirements, offering SOC 2 Type II compliance, HIPAA-ready infrastructure, GDPR-aligned processing, and a 99.9% uptime SLA. Companies across finance, healthcare, legal AI, SaaS, and decentralized AI rely on Phala to enable use cases requiring absolute data confidentiality. With rapid adoption and strong performance, Phala delivers the secure foundation needed for trustworthy AI.
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NVIDIA Confidential Computing
NVIDIA Confidential Computing safeguards data while it is actively being processed, ensuring the protection of AI models and workloads during execution by utilizing hardware-based trusted execution environments integrated within the NVIDIA Hopper and Blackwell architectures, as well as compatible platforms. This innovative solution allows businesses to implement AI training and inference seamlessly, whether on-site, in the cloud, or at edge locations, without requiring modifications to the model code, all while maintaining the confidentiality and integrity of both their data and models. Among its notable features are the zero-trust isolation that keeps workloads separate from the host operating system or hypervisor, device attestation that confirms only authorized NVIDIA hardware is executing the code, and comprehensive compatibility with shared or remote infrastructures, catering to ISVs, enterprises, and multi-tenant setups. By protecting sensitive AI models, inputs, weights, and inference processes, NVIDIA Confidential Computing facilitates the execution of high-performance AI applications without sacrificing security or efficiency. This capability empowers organizations to innovate confidently, knowing their proprietary information remains secure throughout the entire operational lifecycle.
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Pricing
Pricing Starts At:
€5/1M tokens
Pricing Information:
API: €5/1M tokens
Free Trial:
Yes
Integrations
API:
Yes, Privatemode AI has an API
No Integrations at this time
Company Details
Company:
Privatemode
Headquarters:
Germany
Website:
www.privatemode.ai/
Media
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Product Details
Platforms
Windows
Mac
Types of Training
Training Docs
Customer Support
Online Support
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