Search Results for "private cloud"

Private Mind is a mobile AI app built around fully offline, on-device intelligence. It is designed for users who want AI conversations without sending personal data to cloud servers. The app keeps conversations and data on the device, which makes it useful for privacy-sensitive workflows, personal notes, local assistance, and offline use.

Rhino is Picovoice's Speech-to-Intent engine. It directly infers intent from spoken commands within a given context of interest, in real-time. The end-to-end platform for embedding private voice AI into any software in a few lines of code. Design with no limits on top of a modular platform. Create use-case-specific voice AI models in seconds. Develop voice features with a few lines of code using intuitive and cross-platform SDKs. Deliver voice AI everywhere: on-device, mobile, web browsers, on-premise, or cloud. Measure adoption, learn, and iterate. ...

...It is built for production-oriented local LLM execution across Android, iOS, desktop, web, embedded, and IoT environments. The framework focuses on performance, hardware acceleration, and efficient model serving close to the user instead of relying only on remote cloud inference. It supports CPU execution across major platforms and adds GPU or NPU acceleration where available. LiteRT-LM is especially relevant for developers building private, low-latency AI features on phones, laptops, Raspberry Pi-style devices, and other edge hardware. Its goal is to make modern language models usable in local applications with a consistent deployment stack.

Enchanted is an open-source, cross-platform application built to let users chat with privately hosted large language models from Apple devices, including macOS, iOS, and visionOS. Designed to work seamlessly with servers like Ollama, it provides a privacy-focused alternative to traditional cloud AI UIs by connecting directly to your own LLM endpoints such as Llama, Mistral, Vicuna, and more. The interface resembles familiar commercial chat apps but emphasizes local control, offline...

LLMFarm is a framework designed to simplify the deployment, management, and utilization of large language models in local or self-hosted environments, focusing on accessibility and efficient resource usage. It enables users to run LLMs on personal hardware or private infrastructure, reducing dependency on external APIs and improving data privacy. The system typically provides a user-friendly interface for loading models, configuring inference parameters, and interacting with them through...

Every product in the Google Cloud family described in <=4 words (with liberal use of hyphens and slashes) by the Google Developer Relations Team. This list only includes products that are publicly available. There are several products in pre-release/private-alpha that will not be included until they go public beta or GA. Many of these products have a free tier. There is also a free trial that will enable you try almost everything.