Use AI without compromising data security or privacy. End-to-end encrypted AI service for chat, coding, and more.
Privatemode AI is the first AI service that protects the confidentiality of your data end-to-end using confidential computing. It encrypts data before it leaves your device and keeps it protected even during AI processing. It offers encrypted chat, coding assistance, speech-to-text, and an inference API, all with end-to-end encryption. It is built on Edgeless Systems' confidential computing platform and is used in healthcare, public sector, and other regulated industries. It is GDPR compliant and ISO 27001 certified.
Key Features
check_circleEnd-to-end encryption
check_circleConfidential computing
check_circleEncrypted chat
check_circleAI coding assistance
check_circleSpeech-to-text transcription
check_circleInference API
check_circleOpenAI- and Anthropic-compatible API
check_circleIntegrations with n8n, AnythingLLM, Claude Code, VS Code
check_circleGDPR compliant
check_circleISO 27001 certified
check_circleEU-hosted
check_circleNo training on user data
check_circleIndependent security audits
Use Cases
lightbulbHealthcare professionals use Privatemode Chat to ask sensitive medical questions without exposing patient data, ensuring compliance with HIPAA and GDPR.
lightbulbSoftware developers leverage Privatemode's encrypted coding assistant to review and fix proprietary code, preventing leaks of intellectual property.
lightbulbLegal teams transcribe confidential client interviews using speech-to-text, keeping all audio and text encrypted end-to-end.
lightbulbFinancial analysts run AI models on sensitive market data via the inference API, maintaining data confidentiality even during processing.
lightbulbGovernment agencies deploy Privatemode for secure AI workflows, meeting strict regulatory requirements for data handling.
lightbulbCustomer support teams integrate Privatemode with n8n to automate responses while ensuring customer data remains private.
lightbulbResearchers use encrypted chat to discuss unpublished findings without risk of data exposure or model training.
