SentinelAI unveils zero-knowledge inference for privacy-first recommendation engines

AI · 5 min read

SentinelAI introduced a zero-knowledge inference platform that enables personalization models to infer recommendations without exposing raw user data to the model host. The product is positioned for companies needing personalized UX while adhering to strict privacy and compliance requirements.

Alongside the product, SentinelAI raised $48 million in Series B funding to expand engineering and compliance teams. The platform uses cryptographic techniques and split-execution pipelines to keep sensitive attributes on-device or within customer-controlled enclaves.

Designers and product leads see the tech as enabling personalized micro-interactions—curation, onboarding flows and contextual nudge strategies—without risky data centralization. SentinelAI will focus on integrations with e-commerce and media platforms first.