YAME vs Yebo

YAME is an intelligent assistant app built upon the latest on-device Vision Large Language Model. Designed for the visually impaired, YAME helps users perceive and understand the world through state-of-the-art vision-language AI. Key Features • Image Description: Understand your surroundings with detailed visual descriptions. • Facial Expression Recognition: Detect emotions from facial expressions to aid social interaction. • Traffic Signal Detection: Identify traffic light states for safer navigation. • Text-to-Speech (TTS): All results are read aloud instantly, providing seamless audio feedback. Private by Design – Offline AI All processing is done 100% on-device. No internet connection is required, and no images or personal data are ever uploaded or shared. YAME is built with privacy at its core. Device Requirements Due to the high memory demand of on-device AI inference, YAME is recommended for use on the following devices: Compatible iPhones: • iPhone 12 Pro / 12 Pro Max • iPhone 13 Pro / 13 Pro Max • iPhone 14 / 14 Plus / 14 Pro / 14 Pro Max • iPhone 15 / 15 Plus / 15 Pro / 15 Pro Max • iPhone 16 / 16 Plus / 16 Pro / 16 Pro Max Compatible iPads: • iPad Air (5th Gen, M1 chip) • iPad Pro 11-inch (3rd Gen and later, M1 or M2 chip) • iPad Pro 12.9-inch (5th Gen and later, M1 or M2 chip) Note: Devices with less than 6GB RAM (e.g., iPhone 12 or earlier, non-Pro iPads) may not run the model reliably. For best performance and stability, please use a supported device.

AI agents are becoming powerful enough to negotiate tasks, plan workflows, and interact with services across the internet. But when an agent reaches the moment where it needs to execute a real-world action such as sending a payment, committing to a contract, or triggering an external API . Developers need a reliable way to verify that the action is allowed before it happens. Yebo provides that control layer. Yebo acts as an authorization and orchestration system for AI agents and autonomous workflows. Developers connect their AI systems using a simple API, and when an agent wants to perform a sensitive action, the request is routed through Yebo first. Yebo evaluates the request against developer-defined policies, checking permissions, allowed capabilities, budgets, and execution conditions. If the request meets the policy rules, the action is authorized. If not, it is blocked automatically. This approach allows developers to safely connect AI agents to real-world systems without giving those agents unrestricted access. The AI continues to think, plan, and reason normally but any action involving payments, contracts, or protected services must pass through Yebo's verification layer. Yebo is designed to integrate easily with modern AI architectures, including agent frameworks and autonomous systems. Instead of redesigning their agents, developers simply add Yebo to the execution path, enforcing policies and maintaining full control over what actions are permitted. Every authorized action generates a verifiable execution record, allowing teams to review what the agent did and why it was approved. This maintains trust and accountability when deploying AI systems that interact with real services. AI agents can decide what to do. Yebo ensures those decisions are safe to execute.